diff --git a/.gitmodules b/.gitmodules index 26824cb57ff..b4673f113b7 100644 --- a/.gitmodules +++ b/.gitmodules @@ -327,3 +327,6 @@ [submodule "contrib/aws-s2n-tls"] path = contrib/aws-s2n-tls url = https://github.com/ClickHouse/s2n-tls +[submodule "contrib/crc32-vpmsum"] + path = contrib/crc32-vpmsum + url = https://github.com/antonblanchard/crc32-vpmsum.git diff --git a/contrib/CMakeLists.txt b/contrib/CMakeLists.txt index 27b4a7ddb5c..f5d1315cc02 100644 --- a/contrib/CMakeLists.txt +++ b/contrib/CMakeLists.txt @@ -55,6 +55,7 @@ else () endif () add_contrib (miniselect-cmake miniselect) add_contrib (pdqsort-cmake pdqsort) +add_contrib (crc32-vpmsum-cmake crc32-vpmsum) add_contrib (sparsehash-c11-cmake sparsehash-c11) add_contrib (abseil-cpp-cmake abseil-cpp) add_contrib (magic-enum-cmake magic_enum) diff --git a/contrib/crc32-vpmsum b/contrib/crc32-vpmsum new file mode 160000 index 00000000000..45215543938 --- /dev/null +++ b/contrib/crc32-vpmsum @@ -0,0 +1 @@ +Subproject commit 452155439389311fc7d143621eaf56a258e02476 diff --git a/contrib/crc32-vpmsum-cmake/CMakeLists.txt b/contrib/crc32-vpmsum-cmake/CMakeLists.txt new file mode 100644 index 00000000000..bb7d5618410 --- /dev/null +++ b/contrib/crc32-vpmsum-cmake/CMakeLists.txt @@ -0,0 +1,12 @@ +if (NOT ARCH_PPC64LE) + message(STATUS "crc32-vpmsum library is only supported on ppc64le") + return() +endif() + +SET(LIBRARY_DIR "${ClickHouse_SOURCE_DIR}/contrib/crc32-vpmsum") + +add_library(_crc32-vpmsum + "${LIBRARY_DIR}/vec_crc32.c" + ) +target_include_directories(_crc32-vpmsum SYSTEM BEFORE PUBLIC "${CMAKE_CURRENT_SOURCE_DIR}") +add_library(ch_contrib::crc32-vpmsum ALIAS _crc32-vpmsum) diff --git a/contrib/crc32-vpmsum-cmake/README.md b/contrib/crc32-vpmsum-cmake/README.md new file mode 100644 index 00000000000..9ea8133e331 --- /dev/null +++ b/contrib/crc32-vpmsum-cmake/README.md @@ -0,0 +1,8 @@ +# To Generate crc32_constants.h + +- Run make file in `../crc32-vpmsum` diretory using folling options and CRC polynomial. These options should use the same polynomial and order used by intel intrinisic functions +```bash +make crc32_constants.h CRC="0x11EDC6F41" OPTIONS="-x -r -c" +``` +- move the generated `crc32_constants.h` into this directory +- To understand more about this go here: https://masterchef2209.wordpress.com/2020/06/17/guide-to-intel-sse4-2-crc-intrinisics-implementation-for-simde/ diff --git a/contrib/crc32-vpmsum-cmake/crc32_constants.h b/contrib/crc32-vpmsum-cmake/crc32_constants.h new file mode 100644 index 00000000000..aea525c9038 --- /dev/null +++ b/contrib/crc32-vpmsum-cmake/crc32_constants.h @@ -0,0 +1,1206 @@ +/* +* +* THIS FILE IS GENERATED WITH +./crc32_constants -x -r -c 0x11EDC6F41 + +* This is from https://github.com/antonblanchard/crc32-vpmsum/ +* DO NOT MODIFY IT MANUALLY! +* +*/ + +#define CRC 0x1edc6f41 +#define CRC_XOR +#define REFLECT +#define MAX_SIZE 32768 + +#ifndef __ASSEMBLER__ +#ifdef CRC_TABLE +static const unsigned int crc_table[] = { + 0x00000000, 0xf26b8303, 0xe13b70f7, 0x1350f3f4, + 0xc79a971f, 0x35f1141c, 0x26a1e7e8, 0xd4ca64eb, + 0x8ad958cf, 0x78b2dbcc, 0x6be22838, 0x9989ab3b, + 0x4d43cfd0, 0xbf284cd3, 0xac78bf27, 0x5e133c24, + 0x105ec76f, 0xe235446c, 0xf165b798, 0x030e349b, + 0xd7c45070, 0x25afd373, 0x36ff2087, 0xc494a384, + 0x9a879fa0, 0x68ec1ca3, 0x7bbcef57, 0x89d76c54, + 0x5d1d08bf, 0xaf768bbc, 0xbc267848, 0x4e4dfb4b, + 0x20bd8ede, 0xd2d60ddd, 0xc186fe29, 0x33ed7d2a, + 0xe72719c1, 0x154c9ac2, 0x061c6936, 0xf477ea35, + 0xaa64d611, 0x580f5512, 0x4b5fa6e6, 0xb93425e5, + 0x6dfe410e, 0x9f95c20d, 0x8cc531f9, 0x7eaeb2fa, + 0x30e349b1, 0xc288cab2, 0xd1d83946, 0x23b3ba45, + 0xf779deae, 0x05125dad, 0x1642ae59, 0xe4292d5a, + 0xba3a117e, 0x4851927d, 0x5b016189, 0xa96ae28a, + 0x7da08661, 0x8fcb0562, 0x9c9bf696, 0x6ef07595, + 0x417b1dbc, 0xb3109ebf, 0xa0406d4b, 0x522bee48, + 0x86e18aa3, 0x748a09a0, 0x67dafa54, 0x95b17957, + 0xcba24573, 0x39c9c670, 0x2a993584, 0xd8f2b687, + 0x0c38d26c, 0xfe53516f, 0xed03a29b, 0x1f682198, + 0x5125dad3, 0xa34e59d0, 0xb01eaa24, 0x42752927, + 0x96bf4dcc, 0x64d4cecf, 0x77843d3b, 0x85efbe38, + 0xdbfc821c, 0x2997011f, 0x3ac7f2eb, 0xc8ac71e8, + 0x1c661503, 0xee0d9600, 0xfd5d65f4, 0x0f36e6f7, + 0x61c69362, 0x93ad1061, 0x80fde395, 0x72966096, + 0xa65c047d, 0x5437877e, 0x4767748a, 0xb50cf789, + 0xeb1fcbad, 0x197448ae, 0x0a24bb5a, 0xf84f3859, + 0x2c855cb2, 0xdeeedfb1, 0xcdbe2c45, 0x3fd5af46, + 0x7198540d, 0x83f3d70e, 0x90a324fa, 0x62c8a7f9, + 0xb602c312, 0x44694011, 0x5739b3e5, 0xa55230e6, + 0xfb410cc2, 0x092a8fc1, 0x1a7a7c35, 0xe811ff36, + 0x3cdb9bdd, 0xceb018de, 0xdde0eb2a, 0x2f8b6829, + 0x82f63b78, 0x709db87b, 0x63cd4b8f, 0x91a6c88c, + 0x456cac67, 0xb7072f64, 0xa457dc90, 0x563c5f93, + 0x082f63b7, 0xfa44e0b4, 0xe9141340, 0x1b7f9043, + 0xcfb5f4a8, 0x3dde77ab, 0x2e8e845f, 0xdce5075c, + 0x92a8fc17, 0x60c37f14, 0x73938ce0, 0x81f80fe3, + 0x55326b08, 0xa759e80b, 0xb4091bff, 0x466298fc, + 0x1871a4d8, 0xea1a27db, 0xf94ad42f, 0x0b21572c, + 0xdfeb33c7, 0x2d80b0c4, 0x3ed04330, 0xccbbc033, + 0xa24bb5a6, 0x502036a5, 0x4370c551, 0xb11b4652, + 0x65d122b9, 0x97baa1ba, 0x84ea524e, 0x7681d14d, + 0x2892ed69, 0xdaf96e6a, 0xc9a99d9e, 0x3bc21e9d, + 0xef087a76, 0x1d63f975, 0x0e330a81, 0xfc588982, + 0xb21572c9, 0x407ef1ca, 0x532e023e, 0xa145813d, + 0x758fe5d6, 0x87e466d5, 0x94b49521, 0x66df1622, + 0x38cc2a06, 0xcaa7a905, 0xd9f75af1, 0x2b9cd9f2, + 0xff56bd19, 0x0d3d3e1a, 0x1e6dcdee, 0xec064eed, + 0xc38d26c4, 0x31e6a5c7, 0x22b65633, 0xd0ddd530, + 0x0417b1db, 0xf67c32d8, 0xe52cc12c, 0x1747422f, + 0x49547e0b, 0xbb3ffd08, 0xa86f0efc, 0x5a048dff, + 0x8ecee914, 0x7ca56a17, 0x6ff599e3, 0x9d9e1ae0, + 0xd3d3e1ab, 0x21b862a8, 0x32e8915c, 0xc083125f, + 0x144976b4, 0xe622f5b7, 0xf5720643, 0x07198540, + 0x590ab964, 0xab613a67, 0xb831c993, 0x4a5a4a90, + 0x9e902e7b, 0x6cfbad78, 0x7fab5e8c, 0x8dc0dd8f, + 0xe330a81a, 0x115b2b19, 0x020bd8ed, 0xf0605bee, + 0x24aa3f05, 0xd6c1bc06, 0xc5914ff2, 0x37faccf1, + 0x69e9f0d5, 0x9b8273d6, 0x88d28022, 0x7ab90321, + 0xae7367ca, 0x5c18e4c9, 0x4f48173d, 0xbd23943e, + 0xf36e6f75, 0x0105ec76, 0x12551f82, 0xe03e9c81, + 0x34f4f86a, 0xc69f7b69, 0xd5cf889d, 0x27a40b9e, + 0x79b737ba, 0x8bdcb4b9, 0x988c474d, 0x6ae7c44e, + 0xbe2da0a5, 0x4c4623a6, 0x5f16d052, 0xad7d5351,}; + +#endif /* CRC_TABLE */ +#ifdef POWER8_INTRINSICS + +/* Constants */ + +/* Reduce 262144 kbits to 1024 bits */ +static const __vector unsigned long long vcrc_const[255] + __attribute__((aligned (16))) = { +#ifdef __LITTLE_ENDIAN__ + /* x^261120 mod p(x)` << 1, x^261184 mod p(x)` << 1 */ + { 0x000000009c37c408, 0x00000000b6ca9e20 }, + /* x^260096 mod p(x)` << 1, x^260160 mod p(x)` << 1 */ + { 0x00000001b51df26c, 0x00000000350249a8 }, + /* x^259072 mod p(x)` << 1, x^259136 mod p(x)` << 1 */ + { 0x000000000724b9d0, 0x00000001862dac54 }, + /* x^258048 mod p(x)` << 1, x^258112 mod p(x)` << 1 */ + { 0x00000001c00532fe, 0x00000001d87fb48c }, + /* x^257024 mod p(x)` << 1, x^257088 mod p(x)` << 1 */ + { 0x00000000f05a9362, 0x00000001f39b699e }, + /* x^256000 mod p(x)` << 1, x^256064 mod p(x)` << 1 */ + { 0x00000001e1007970, 0x0000000101da11b4 }, + /* x^254976 mod p(x)` << 1, x^255040 mod p(x)` << 1 */ + { 0x00000000a57366ee, 0x00000001cab571e0 }, + /* x^253952 mod p(x)` << 1, x^254016 mod p(x)` << 1 */ + { 0x0000000192011284, 0x00000000c7020cfe }, + /* x^252928 mod p(x)` << 1, x^252992 mod p(x)` << 1 */ + { 0x0000000162716d9a, 0x00000000cdaed1ae }, + /* x^251904 mod p(x)` << 1, x^251968 mod p(x)` << 1 */ + { 0x00000000cd97ecde, 0x00000001e804effc }, + /* x^250880 mod p(x)` << 1, x^250944 mod p(x)` << 1 */ + { 0x0000000058812bc0, 0x0000000077c3ea3a }, + /* x^249856 mod p(x)` << 1, x^249920 mod p(x)` << 1 */ + { 0x0000000088b8c12e, 0x0000000068df31b4 }, + /* x^248832 mod p(x)` << 1, x^248896 mod p(x)` << 1 */ + { 0x00000001230b234c, 0x00000000b059b6c2 }, + /* x^247808 mod p(x)` << 1, x^247872 mod p(x)` << 1 */ + { 0x00000001120b416e, 0x0000000145fb8ed8 }, + /* x^246784 mod p(x)` << 1, x^246848 mod p(x)` << 1 */ + { 0x00000001974aecb0, 0x00000000cbc09168 }, + /* x^245760 mod p(x)` << 1, x^245824 mod p(x)` << 1 */ + { 0x000000008ee3f226, 0x000000005ceeedc2 }, + /* x^244736 mod p(x)` << 1, x^244800 mod p(x)` << 1 */ + { 0x00000001089aba9a, 0x0000000047d74e86 }, + /* x^243712 mod p(x)` << 1, x^243776 mod p(x)` << 1 */ + { 0x0000000065113872, 0x00000001407e9e22 }, + /* x^242688 mod p(x)` << 1, x^242752 mod p(x)` << 1 */ + { 0x000000005c07ec10, 0x00000001da967bda }, + /* x^241664 mod p(x)` << 1, x^241728 mod p(x)` << 1 */ + { 0x0000000187590924, 0x000000006c898368 }, + /* x^240640 mod p(x)` << 1, x^240704 mod p(x)` << 1 */ + { 0x00000000e35da7c6, 0x00000000f2d14c98 }, + /* x^239616 mod p(x)` << 1, x^239680 mod p(x)` << 1 */ + { 0x000000000415855a, 0x00000001993c6ad4 }, + /* x^238592 mod p(x)` << 1, x^238656 mod p(x)` << 1 */ + { 0x0000000073617758, 0x000000014683d1ac }, + /* x^237568 mod p(x)` << 1, x^237632 mod p(x)` << 1 */ + { 0x0000000176021d28, 0x00000001a7c93e6c }, + /* x^236544 mod p(x)` << 1, x^236608 mod p(x)` << 1 */ + { 0x00000001c358fd0a, 0x000000010211e90a }, + /* x^235520 mod p(x)` << 1, x^235584 mod p(x)` << 1 */ + { 0x00000001ff7a2c18, 0x000000001119403e }, + /* x^234496 mod p(x)` << 1, x^234560 mod p(x)` << 1 */ + { 0x00000000f2d9f7e4, 0x000000001c3261aa }, + /* x^233472 mod p(x)` << 1, x^233536 mod p(x)` << 1 */ + { 0x000000016cf1f9c8, 0x000000014e37a634 }, + /* x^232448 mod p(x)` << 1, x^232512 mod p(x)` << 1 */ + { 0x000000010af9279a, 0x0000000073786c0c }, + /* x^231424 mod p(x)` << 1, x^231488 mod p(x)` << 1 */ + { 0x0000000004f101e8, 0x000000011dc037f8 }, + /* x^230400 mod p(x)` << 1, x^230464 mod p(x)` << 1 */ + { 0x0000000070bcf184, 0x0000000031433dfc }, + /* x^229376 mod p(x)` << 1, x^229440 mod p(x)` << 1 */ + { 0x000000000a8de642, 0x000000009cde8348 }, + /* x^228352 mod p(x)` << 1, x^228416 mod p(x)` << 1 */ + { 0x0000000062ea130c, 0x0000000038d3c2a6 }, + /* x^227328 mod p(x)` << 1, x^227392 mod p(x)` << 1 */ + { 0x00000001eb31cbb2, 0x000000011b25f260 }, + /* x^226304 mod p(x)` << 1, x^226368 mod p(x)` << 1 */ + { 0x0000000170783448, 0x000000001629e6f0 }, + /* x^225280 mod p(x)` << 1, x^225344 mod p(x)` << 1 */ + { 0x00000001a684b4c6, 0x0000000160838b4c }, + /* x^224256 mod p(x)` << 1, x^224320 mod p(x)` << 1 */ + { 0x00000000253ca5b4, 0x000000007a44011c }, + /* x^223232 mod p(x)` << 1, x^223296 mod p(x)` << 1 */ + { 0x0000000057b4b1e2, 0x00000000226f417a }, + /* x^222208 mod p(x)` << 1, x^222272 mod p(x)` << 1 */ + { 0x00000000b6bd084c, 0x0000000045eb2eb4 }, + /* x^221184 mod p(x)` << 1, x^221248 mod p(x)` << 1 */ + { 0x0000000123c2d592, 0x000000014459d70c }, + /* x^220160 mod p(x)` << 1, x^220224 mod p(x)` << 1 */ + { 0x00000000159dafce, 0x00000001d406ed82 }, + /* x^219136 mod p(x)` << 1, x^219200 mod p(x)` << 1 */ + { 0x0000000127e1a64e, 0x0000000160c8e1a8 }, + /* x^218112 mod p(x)` << 1, x^218176 mod p(x)` << 1 */ + { 0x0000000056860754, 0x0000000027ba8098 }, + /* x^217088 mod p(x)` << 1, x^217152 mod p(x)` << 1 */ + { 0x00000001e661aae8, 0x000000006d92d018 }, + /* x^216064 mod p(x)` << 1, x^216128 mod p(x)` << 1 */ + { 0x00000000f82c6166, 0x000000012ed7e3f2 }, + /* x^215040 mod p(x)` << 1, x^215104 mod p(x)` << 1 */ + { 0x00000000c4f9c7ae, 0x000000002dc87788 }, + /* x^214016 mod p(x)` << 1, x^214080 mod p(x)` << 1 */ + { 0x0000000074203d20, 0x0000000018240bb8 }, + /* x^212992 mod p(x)` << 1, x^213056 mod p(x)` << 1 */ + { 0x0000000198173052, 0x000000001ad38158 }, + /* x^211968 mod p(x)` << 1, x^212032 mod p(x)` << 1 */ + { 0x00000001ce8aba54, 0x00000001396b78f2 }, + /* x^210944 mod p(x)` << 1, x^211008 mod p(x)` << 1 */ + { 0x00000001850d5d94, 0x000000011a681334 }, + /* x^209920 mod p(x)` << 1, x^209984 mod p(x)` << 1 */ + { 0x00000001d609239c, 0x000000012104732e }, + /* x^208896 mod p(x)` << 1, x^208960 mod p(x)` << 1 */ + { 0x000000001595f048, 0x00000000a140d90c }, + /* x^207872 mod p(x)` << 1, x^207936 mod p(x)` << 1 */ + { 0x0000000042ccee08, 0x00000001b7215eda }, + /* x^206848 mod p(x)` << 1, x^206912 mod p(x)` << 1 */ + { 0x000000010a389d74, 0x00000001aaf1df3c }, + /* x^205824 mod p(x)` << 1, x^205888 mod p(x)` << 1 */ + { 0x000000012a840da6, 0x0000000029d15b8a }, + /* x^204800 mod p(x)` << 1, x^204864 mod p(x)` << 1 */ + { 0x000000001d181c0c, 0x00000000f1a96922 }, + /* x^203776 mod p(x)` << 1, x^203840 mod p(x)` << 1 */ + { 0x0000000068b7d1f6, 0x00000001ac80d03c }, + /* x^202752 mod p(x)` << 1, x^202816 mod p(x)` << 1 */ + { 0x000000005b0f14fc, 0x000000000f11d56a }, + /* x^201728 mod p(x)` << 1, x^201792 mod p(x)` << 1 */ + { 0x0000000179e9e730, 0x00000001f1c022a2 }, + /* x^200704 mod p(x)` << 1, x^200768 mod p(x)` << 1 */ + { 0x00000001ce1368d6, 0x0000000173d00ae2 }, + /* x^199680 mod p(x)` << 1, x^199744 mod p(x)` << 1 */ + { 0x0000000112c3a84c, 0x00000001d4ffe4ac }, + /* x^198656 mod p(x)` << 1, x^198720 mod p(x)` << 1 */ + { 0x00000000de940fee, 0x000000016edc5ae4 }, + /* x^197632 mod p(x)` << 1, x^197696 mod p(x)` << 1 */ + { 0x00000000fe896b7e, 0x00000001f1a02140 }, + /* x^196608 mod p(x)` << 1, x^196672 mod p(x)` << 1 */ + { 0x00000001f797431c, 0x00000000ca0b28a0 }, + /* x^195584 mod p(x)` << 1, x^195648 mod p(x)` << 1 */ + { 0x0000000053e989ba, 0x00000001928e30a2 }, + /* x^194560 mod p(x)` << 1, x^194624 mod p(x)` << 1 */ + { 0x000000003920cd16, 0x0000000097b1b002 }, + /* x^193536 mod p(x)` << 1, x^193600 mod p(x)` << 1 */ + { 0x00000001e6f579b8, 0x00000000b15bf906 }, + /* x^192512 mod p(x)` << 1, x^192576 mod p(x)` << 1 */ + { 0x000000007493cb0a, 0x00000000411c5d52 }, + /* x^191488 mod p(x)` << 1, x^191552 mod p(x)` << 1 */ + { 0x00000001bdd376d8, 0x00000001c36f3300 }, + /* x^190464 mod p(x)` << 1, x^190528 mod p(x)` << 1 */ + { 0x000000016badfee6, 0x00000001119227e0 }, + /* x^189440 mod p(x)` << 1, x^189504 mod p(x)` << 1 */ + { 0x0000000071de5c58, 0x00000000114d4702 }, + /* x^188416 mod p(x)` << 1, x^188480 mod p(x)` << 1 */ + { 0x00000000453f317c, 0x00000000458b5b98 }, + /* x^187392 mod p(x)` << 1, x^187456 mod p(x)` << 1 */ + { 0x0000000121675cce, 0x000000012e31fb8e }, + /* x^186368 mod p(x)` << 1, x^186432 mod p(x)` << 1 */ + { 0x00000001f409ee92, 0x000000005cf619d8 }, + /* x^185344 mod p(x)` << 1, x^185408 mod p(x)` << 1 */ + { 0x00000000f36b9c88, 0x0000000063f4d8b2 }, + /* x^184320 mod p(x)` << 1, x^184384 mod p(x)` << 1 */ + { 0x0000000036b398f4, 0x000000004138dc8a }, + /* x^183296 mod p(x)` << 1, x^183360 mod p(x)` << 1 */ + { 0x00000001748f9adc, 0x00000001d29ee8e0 }, + /* x^182272 mod p(x)` << 1, x^182336 mod p(x)` << 1 */ + { 0x00000001be94ec00, 0x000000006a08ace8 }, + /* x^181248 mod p(x)` << 1, x^181312 mod p(x)` << 1 */ + { 0x00000000b74370d6, 0x0000000127d42010 }, + /* x^180224 mod p(x)` << 1, x^180288 mod p(x)` << 1 */ + { 0x00000001174d0b98, 0x0000000019d76b62 }, + /* x^179200 mod p(x)` << 1, x^179264 mod p(x)` << 1 */ + { 0x00000000befc06a4, 0x00000001b1471f6e }, + /* x^178176 mod p(x)` << 1, x^178240 mod p(x)` << 1 */ + { 0x00000001ae125288, 0x00000001f64c19cc }, + /* x^177152 mod p(x)` << 1, x^177216 mod p(x)` << 1 */ + { 0x0000000095c19b34, 0x00000000003c0ea0 }, + /* x^176128 mod p(x)` << 1, x^176192 mod p(x)` << 1 */ + { 0x00000001a78496f2, 0x000000014d73abf6 }, + /* x^175104 mod p(x)` << 1, x^175168 mod p(x)` << 1 */ + { 0x00000001ac5390a0, 0x00000001620eb844 }, + /* x^174080 mod p(x)` << 1, x^174144 mod p(x)` << 1 */ + { 0x000000002a80ed6e, 0x0000000147655048 }, + /* x^173056 mod p(x)` << 1, x^173120 mod p(x)` << 1 */ + { 0x00000001fa9b0128, 0x0000000067b5077e }, + /* x^172032 mod p(x)` << 1, x^172096 mod p(x)` << 1 */ + { 0x00000001ea94929e, 0x0000000010ffe206 }, + /* x^171008 mod p(x)` << 1, x^171072 mod p(x)` << 1 */ + { 0x0000000125f4305c, 0x000000000fee8f1e }, + /* x^169984 mod p(x)` << 1, x^170048 mod p(x)` << 1 */ + { 0x00000001471e2002, 0x00000001da26fbae }, + /* x^168960 mod p(x)` << 1, x^169024 mod p(x)` << 1 */ + { 0x0000000132d2253a, 0x00000001b3a8bd88 }, + /* x^167936 mod p(x)` << 1, x^168000 mod p(x)` << 1 */ + { 0x00000000f26b3592, 0x00000000e8f3898e }, + /* x^166912 mod p(x)` << 1, x^166976 mod p(x)` << 1 */ + { 0x00000000bc8b67b0, 0x00000000b0d0d28c }, + /* x^165888 mod p(x)` << 1, x^165952 mod p(x)` << 1 */ + { 0x000000013a826ef2, 0x0000000030f2a798 }, + /* x^164864 mod p(x)` << 1, x^164928 mod p(x)` << 1 */ + { 0x0000000081482c84, 0x000000000fba1002 }, + /* x^163840 mod p(x)` << 1, x^163904 mod p(x)` << 1 */ + { 0x00000000e77307c2, 0x00000000bdb9bd72 }, + /* x^162816 mod p(x)` << 1, x^162880 mod p(x)` << 1 */ + { 0x00000000d4a07ec8, 0x0000000075d3bf5a }, + /* x^161792 mod p(x)` << 1, x^161856 mod p(x)` << 1 */ + { 0x0000000017102100, 0x00000000ef1f98a0 }, + /* x^160768 mod p(x)` << 1, x^160832 mod p(x)` << 1 */ + { 0x00000000db406486, 0x00000000689c7602 }, + /* x^159744 mod p(x)` << 1, x^159808 mod p(x)` << 1 */ + { 0x0000000192db7f88, 0x000000016d5fa5fe }, + /* x^158720 mod p(x)` << 1, x^158784 mod p(x)` << 1 */ + { 0x000000018bf67b1e, 0x00000001d0d2b9ca }, + /* x^157696 mod p(x)` << 1, x^157760 mod p(x)` << 1 */ + { 0x000000007c09163e, 0x0000000041e7b470 }, + /* x^156672 mod p(x)` << 1, x^156736 mod p(x)` << 1 */ + { 0x000000000adac060, 0x00000001cbb6495e }, + /* x^155648 mod p(x)` << 1, x^155712 mod p(x)` << 1 */ + { 0x00000000bd8316ae, 0x000000010052a0b0 }, + /* x^154624 mod p(x)` << 1, x^154688 mod p(x)` << 1 */ + { 0x000000019f09ab54, 0x00000001d8effb5c }, + /* x^153600 mod p(x)` << 1, x^153664 mod p(x)` << 1 */ + { 0x0000000125155542, 0x00000001d969853c }, + /* x^152576 mod p(x)` << 1, x^152640 mod p(x)` << 1 */ + { 0x000000018fdb5882, 0x00000000523ccce2 }, + /* x^151552 mod p(x)` << 1, x^151616 mod p(x)` << 1 */ + { 0x00000000e794b3f4, 0x000000001e2436bc }, + /* x^150528 mod p(x)` << 1, x^150592 mod p(x)` << 1 */ + { 0x000000016f9bb022, 0x00000000ddd1c3a2 }, + /* x^149504 mod p(x)` << 1, x^149568 mod p(x)` << 1 */ + { 0x00000000290c9978, 0x0000000019fcfe38 }, + /* x^148480 mod p(x)` << 1, x^148544 mod p(x)` << 1 */ + { 0x0000000083c0f350, 0x00000001ce95db64 }, + /* x^147456 mod p(x)` << 1, x^147520 mod p(x)` << 1 */ + { 0x0000000173ea6628, 0x00000000af582806 }, + /* x^146432 mod p(x)` << 1, x^146496 mod p(x)` << 1 */ + { 0x00000001c8b4e00a, 0x00000001006388f6 }, + /* x^145408 mod p(x)` << 1, x^145472 mod p(x)` << 1 */ + { 0x00000000de95d6aa, 0x0000000179eca00a }, + /* x^144384 mod p(x)` << 1, x^144448 mod p(x)` << 1 */ + { 0x000000010b7f7248, 0x0000000122410a6a }, + /* x^143360 mod p(x)` << 1, x^143424 mod p(x)` << 1 */ + { 0x00000001326e3a06, 0x000000004288e87c }, + /* x^142336 mod p(x)` << 1, x^142400 mod p(x)` << 1 */ + { 0x00000000bb62c2e6, 0x000000016c5490da }, + /* x^141312 mod p(x)` << 1, x^141376 mod p(x)` << 1 */ + { 0x0000000156a4b2c2, 0x00000000d1c71f6e }, + /* x^140288 mod p(x)` << 1, x^140352 mod p(x)` << 1 */ + { 0x000000011dfe763a, 0x00000001b4ce08a6 }, + /* x^139264 mod p(x)` << 1, x^139328 mod p(x)` << 1 */ + { 0x000000007bcca8e2, 0x00000001466ba60c }, + /* x^138240 mod p(x)` << 1, x^138304 mod p(x)` << 1 */ + { 0x0000000186118faa, 0x00000001f6c488a4 }, + /* x^137216 mod p(x)` << 1, x^137280 mod p(x)` << 1 */ + { 0x0000000111a65a88, 0x000000013bfb0682 }, + /* x^136192 mod p(x)` << 1, x^136256 mod p(x)` << 1 */ + { 0x000000003565e1c4, 0x00000000690e9e54 }, + /* x^135168 mod p(x)` << 1, x^135232 mod p(x)` << 1 */ + { 0x000000012ed02a82, 0x00000000281346b6 }, + /* x^134144 mod p(x)` << 1, x^134208 mod p(x)` << 1 */ + { 0x00000000c486ecfc, 0x0000000156464024 }, + /* x^133120 mod p(x)` << 1, x^133184 mod p(x)` << 1 */ + { 0x0000000001b951b2, 0x000000016063a8dc }, + /* x^132096 mod p(x)` << 1, x^132160 mod p(x)` << 1 */ + { 0x0000000048143916, 0x0000000116a66362 }, + /* x^131072 mod p(x)` << 1, x^131136 mod p(x)` << 1 */ + { 0x00000001dc2ae124, 0x000000017e8aa4d2 }, + /* x^130048 mod p(x)` << 1, x^130112 mod p(x)` << 1 */ + { 0x00000001416c58d6, 0x00000001728eb10c }, + /* x^129024 mod p(x)` << 1, x^129088 mod p(x)` << 1 */ + { 0x00000000a479744a, 0x00000001b08fd7fa }, + /* x^128000 mod p(x)` << 1, x^128064 mod p(x)` << 1 */ + { 0x0000000096ca3a26, 0x00000001092a16e8 }, + /* x^126976 mod p(x)` << 1, x^127040 mod p(x)` << 1 */ + { 0x00000000ff223d4e, 0x00000000a505637c }, + /* x^125952 mod p(x)` << 1, x^126016 mod p(x)` << 1 */ + { 0x000000010e84da42, 0x00000000d94869b2 }, + /* x^124928 mod p(x)` << 1, x^124992 mod p(x)` << 1 */ + { 0x00000001b61ba3d0, 0x00000001c8b203ae }, + /* x^123904 mod p(x)` << 1, x^123968 mod p(x)` << 1 */ + { 0x00000000680f2de8, 0x000000005704aea0 }, + /* x^122880 mod p(x)` << 1, x^122944 mod p(x)` << 1 */ + { 0x000000008772a9a8, 0x000000012e295fa2 }, + /* x^121856 mod p(x)` << 1, x^121920 mod p(x)` << 1 */ + { 0x0000000155f295bc, 0x000000011d0908bc }, + /* x^120832 mod p(x)` << 1, x^120896 mod p(x)` << 1 */ + { 0x00000000595f9282, 0x0000000193ed97ea }, + /* x^119808 mod p(x)` << 1, x^119872 mod p(x)` << 1 */ + { 0x0000000164b1c25a, 0x000000013a0f1c52 }, + /* x^118784 mod p(x)` << 1, x^118848 mod p(x)` << 1 */ + { 0x00000000fbd67c50, 0x000000010c2c40c0 }, + /* x^117760 mod p(x)` << 1, x^117824 mod p(x)` << 1 */ + { 0x0000000096076268, 0x00000000ff6fac3e }, + /* x^116736 mod p(x)` << 1, x^116800 mod p(x)` << 1 */ + { 0x00000001d288e4cc, 0x000000017b3609c0 }, + /* x^115712 mod p(x)` << 1, x^115776 mod p(x)` << 1 */ + { 0x00000001eaac1bdc, 0x0000000088c8c922 }, + /* x^114688 mod p(x)` << 1, x^114752 mod p(x)` << 1 */ + { 0x00000001f1ea39e2, 0x00000001751baae6 }, + /* x^113664 mod p(x)` << 1, x^113728 mod p(x)` << 1 */ + { 0x00000001eb6506fc, 0x0000000107952972 }, + /* x^112640 mod p(x)` << 1, x^112704 mod p(x)` << 1 */ + { 0x000000010f806ffe, 0x0000000162b00abe }, + /* x^111616 mod p(x)` << 1, x^111680 mod p(x)` << 1 */ + { 0x000000010408481e, 0x000000000d7b404c }, + /* x^110592 mod p(x)` << 1, x^110656 mod p(x)` << 1 */ + { 0x0000000188260534, 0x00000000763b13d4 }, + /* x^109568 mod p(x)` << 1, x^109632 mod p(x)` << 1 */ + { 0x0000000058fc73e0, 0x00000000f6dc22d8 }, + /* x^108544 mod p(x)` << 1, x^108608 mod p(x)` << 1 */ + { 0x00000000391c59b8, 0x000000007daae060 }, + /* x^107520 mod p(x)` << 1, x^107584 mod p(x)` << 1 */ + { 0x000000018b638400, 0x000000013359ab7c }, + /* x^106496 mod p(x)` << 1, x^106560 mod p(x)` << 1 */ + { 0x000000011738f5c4, 0x000000008add438a }, + /* x^105472 mod p(x)` << 1, x^105536 mod p(x)` << 1 */ + { 0x000000008cf7c6da, 0x00000001edbefdea }, + /* x^104448 mod p(x)` << 1, x^104512 mod p(x)` << 1 */ + { 0x00000001ef97fb16, 0x000000004104e0f8 }, + /* x^103424 mod p(x)` << 1, x^103488 mod p(x)` << 1 */ + { 0x0000000102130e20, 0x00000000b48a8222 }, + /* x^102400 mod p(x)` << 1, x^102464 mod p(x)` << 1 */ + { 0x00000000db968898, 0x00000001bcb46844 }, + /* x^101376 mod p(x)` << 1, x^101440 mod p(x)` << 1 */ + { 0x00000000b5047b5e, 0x000000013293ce0a }, + /* x^100352 mod p(x)` << 1, x^100416 mod p(x)` << 1 */ + { 0x000000010b90fdb2, 0x00000001710d0844 }, + /* x^99328 mod p(x)` << 1, x^99392 mod p(x)` << 1 */ + { 0x000000004834a32e, 0x0000000117907f6e }, + /* x^98304 mod p(x)` << 1, x^98368 mod p(x)` << 1 */ + { 0x0000000059c8f2b0, 0x0000000087ddf93e }, + /* x^97280 mod p(x)` << 1, x^97344 mod p(x)` << 1 */ + { 0x0000000122cec508, 0x000000005970e9b0 }, + /* x^96256 mod p(x)` << 1, x^96320 mod p(x)` << 1 */ + { 0x000000000a330cda, 0x0000000185b2b7d0 }, + /* x^95232 mod p(x)` << 1, x^95296 mod p(x)` << 1 */ + { 0x000000014a47148c, 0x00000001dcee0efc }, + /* x^94208 mod p(x)` << 1, x^94272 mod p(x)` << 1 */ + { 0x0000000042c61cb8, 0x0000000030da2722 }, + /* x^93184 mod p(x)` << 1, x^93248 mod p(x)` << 1 */ + { 0x0000000012fe6960, 0x000000012f925a18 }, + /* x^92160 mod p(x)` << 1, x^92224 mod p(x)` << 1 */ + { 0x00000000dbda2c20, 0x00000000dd2e357c }, + /* x^91136 mod p(x)` << 1, x^91200 mod p(x)` << 1 */ + { 0x000000011122410c, 0x00000000071c80de }, + /* x^90112 mod p(x)` << 1, x^90176 mod p(x)` << 1 */ + { 0x00000000977b2070, 0x000000011513140a }, + /* x^89088 mod p(x)` << 1, x^89152 mod p(x)` << 1 */ + { 0x000000014050438e, 0x00000001df876e8e }, + /* x^88064 mod p(x)` << 1, x^88128 mod p(x)` << 1 */ + { 0x0000000147c840e8, 0x000000015f81d6ce }, + /* x^87040 mod p(x)` << 1, x^87104 mod p(x)` << 1 */ + { 0x00000001cc7c88ce, 0x000000019dd94dbe }, + /* x^86016 mod p(x)` << 1, x^86080 mod p(x)` << 1 */ + { 0x00000001476b35a4, 0x00000001373d206e }, + /* x^84992 mod p(x)` << 1, x^85056 mod p(x)` << 1 */ + { 0x000000013d52d508, 0x00000000668ccade }, + /* x^83968 mod p(x)` << 1, x^84032 mod p(x)` << 1 */ + { 0x000000008e4be32e, 0x00000001b192d268 }, + /* x^82944 mod p(x)` << 1, x^83008 mod p(x)` << 1 */ + { 0x00000000024120fe, 0x00000000e30f3a78 }, + /* x^81920 mod p(x)` << 1, x^81984 mod p(x)` << 1 */ + { 0x00000000ddecddb4, 0x000000010ef1f7bc }, + /* x^80896 mod p(x)` << 1, x^80960 mod p(x)` << 1 */ + { 0x00000000d4d403bc, 0x00000001f5ac7380 }, + /* x^79872 mod p(x)` << 1, x^79936 mod p(x)` << 1 */ + { 0x00000001734b89aa, 0x000000011822ea70 }, + /* x^78848 mod p(x)` << 1, x^78912 mod p(x)` << 1 */ + { 0x000000010e7a58d6, 0x00000000c3a33848 }, + /* x^77824 mod p(x)` << 1, x^77888 mod p(x)` << 1 */ + { 0x00000001f9f04e9c, 0x00000001bd151c24 }, + /* x^76800 mod p(x)` << 1, x^76864 mod p(x)` << 1 */ + { 0x00000000b692225e, 0x0000000056002d76 }, + /* x^75776 mod p(x)` << 1, x^75840 mod p(x)` << 1 */ + { 0x000000019b8d3f3e, 0x000000014657c4f4 }, + /* x^74752 mod p(x)` << 1, x^74816 mod p(x)` << 1 */ + { 0x00000001a874f11e, 0x0000000113742d7c }, + /* x^73728 mod p(x)` << 1, x^73792 mod p(x)` << 1 */ + { 0x000000010d5a4254, 0x000000019c5920ba }, + /* x^72704 mod p(x)` << 1, x^72768 mod p(x)` << 1 */ + { 0x00000000bbb2f5d6, 0x000000005216d2d6 }, + /* x^71680 mod p(x)` << 1, x^71744 mod p(x)` << 1 */ + { 0x0000000179cc0e36, 0x0000000136f5ad8a }, + /* x^70656 mod p(x)` << 1, x^70720 mod p(x)` << 1 */ + { 0x00000001dca1da4a, 0x000000018b07beb6 }, + /* x^69632 mod p(x)` << 1, x^69696 mod p(x)` << 1 */ + { 0x00000000feb1a192, 0x00000000db1e93b0 }, + /* x^68608 mod p(x)` << 1, x^68672 mod p(x)` << 1 */ + { 0x00000000d1eeedd6, 0x000000000b96fa3a }, + /* x^67584 mod p(x)` << 1, x^67648 mod p(x)` << 1 */ + { 0x000000008fad9bb4, 0x00000001d9968af0 }, + /* x^66560 mod p(x)` << 1, x^66624 mod p(x)` << 1 */ + { 0x00000001884938e4, 0x000000000e4a77a2 }, + /* x^65536 mod p(x)` << 1, x^65600 mod p(x)` << 1 */ + { 0x00000001bc2e9bc0, 0x00000000508c2ac8 }, + /* x^64512 mod p(x)` << 1, x^64576 mod p(x)` << 1 */ + { 0x00000001f9658a68, 0x0000000021572a80 }, + /* x^63488 mod p(x)` << 1, x^63552 mod p(x)` << 1 */ + { 0x000000001b9224fc, 0x00000001b859daf2 }, + /* x^62464 mod p(x)` << 1, x^62528 mod p(x)` << 1 */ + { 0x0000000055b2fb84, 0x000000016f788474 }, + /* x^61440 mod p(x)` << 1, x^61504 mod p(x)` << 1 */ + { 0x000000018b090348, 0x00000001b438810e }, + /* x^60416 mod p(x)` << 1, x^60480 mod p(x)` << 1 */ + { 0x000000011ccbd5ea, 0x0000000095ddc6f2 }, + /* x^59392 mod p(x)` << 1, x^59456 mod p(x)` << 1 */ + { 0x0000000007ae47f8, 0x00000001d977c20c }, + /* x^58368 mod p(x)` << 1, x^58432 mod p(x)` << 1 */ + { 0x0000000172acbec0, 0x00000000ebedb99a }, + /* x^57344 mod p(x)` << 1, x^57408 mod p(x)` << 1 */ + { 0x00000001c6e3ff20, 0x00000001df9e9e92 }, + /* x^56320 mod p(x)` << 1, x^56384 mod p(x)` << 1 */ + { 0x00000000e1b38744, 0x00000001a4a3f952 }, + /* x^55296 mod p(x)` << 1, x^55360 mod p(x)` << 1 */ + { 0x00000000791585b2, 0x00000000e2f51220 }, + /* x^54272 mod p(x)` << 1, x^54336 mod p(x)` << 1 */ + { 0x00000000ac53b894, 0x000000004aa01f3e }, + /* x^53248 mod p(x)` << 1, x^53312 mod p(x)` << 1 */ + { 0x00000001ed5f2cf4, 0x00000000b3e90a58 }, + /* x^52224 mod p(x)` << 1, x^52288 mod p(x)` << 1 */ + { 0x00000001df48b2e0, 0x000000000c9ca2aa }, + /* x^51200 mod p(x)` << 1, x^51264 mod p(x)` << 1 */ + { 0x00000000049c1c62, 0x0000000151682316 }, + /* x^50176 mod p(x)` << 1, x^50240 mod p(x)` << 1 */ + { 0x000000017c460c12, 0x0000000036fce78c }, + /* x^49152 mod p(x)` << 1, x^49216 mod p(x)` << 1 */ + { 0x000000015be4da7e, 0x000000009037dc10 }, + /* x^48128 mod p(x)` << 1, x^48192 mod p(x)` << 1 */ + { 0x000000010f38f668, 0x00000000d3298582 }, + /* x^47104 mod p(x)` << 1, x^47168 mod p(x)` << 1 */ + { 0x0000000039f40a00, 0x00000001b42e8ad6 }, + /* x^46080 mod p(x)` << 1, x^46144 mod p(x)` << 1 */ + { 0x00000000bd4c10c4, 0x00000000142a9838 }, + /* x^45056 mod p(x)` << 1, x^45120 mod p(x)` << 1 */ + { 0x0000000042db1d98, 0x0000000109c7f190 }, + /* x^44032 mod p(x)` << 1, x^44096 mod p(x)` << 1 */ + { 0x00000001c905bae6, 0x0000000056ff9310 }, + /* x^43008 mod p(x)` << 1, x^43072 mod p(x)` << 1 */ + { 0x00000000069d40ea, 0x00000001594513aa }, + /* x^41984 mod p(x)` << 1, x^42048 mod p(x)` << 1 */ + { 0x000000008e4fbad0, 0x00000001e3b5b1e8 }, + /* x^40960 mod p(x)` << 1, x^41024 mod p(x)` << 1 */ + { 0x0000000047bedd46, 0x000000011dd5fc08 }, + /* x^39936 mod p(x)` << 1, x^40000 mod p(x)` << 1 */ + { 0x0000000026396bf8, 0x00000001675f0cc2 }, + /* x^38912 mod p(x)` << 1, x^38976 mod p(x)` << 1 */ + { 0x00000000379beb92, 0x00000000d1c8dd44 }, + /* x^37888 mod p(x)` << 1, x^37952 mod p(x)` << 1 */ + { 0x000000000abae54a, 0x0000000115ebd3d8 }, + /* x^36864 mod p(x)` << 1, x^36928 mod p(x)` << 1 */ + { 0x0000000007e6a128, 0x00000001ecbd0dac }, + /* x^35840 mod p(x)` << 1, x^35904 mod p(x)` << 1 */ + { 0x000000000ade29d2, 0x00000000cdf67af2 }, + /* x^34816 mod p(x)` << 1, x^34880 mod p(x)` << 1 */ + { 0x00000000f974c45c, 0x000000004c01ff4c }, + /* x^33792 mod p(x)` << 1, x^33856 mod p(x)` << 1 */ + { 0x00000000e77ac60a, 0x00000000f2d8657e }, + /* x^32768 mod p(x)` << 1, x^32832 mod p(x)` << 1 */ + { 0x0000000145895816, 0x000000006bae74c4 }, + /* x^31744 mod p(x)` << 1, x^31808 mod p(x)` << 1 */ + { 0x0000000038e362be, 0x0000000152af8aa0 }, + /* x^30720 mod p(x)` << 1, x^30784 mod p(x)` << 1 */ + { 0x000000007f991a64, 0x0000000004663802 }, + /* x^29696 mod p(x)` << 1, x^29760 mod p(x)` << 1 */ + { 0x00000000fa366d3a, 0x00000001ab2f5afc }, + /* x^28672 mod p(x)` << 1, x^28736 mod p(x)` << 1 */ + { 0x00000001a2bb34f0, 0x0000000074a4ebd4 }, + /* x^27648 mod p(x)` << 1, x^27712 mod p(x)` << 1 */ + { 0x0000000028a9981e, 0x00000001d7ab3a4c }, + /* x^26624 mod p(x)` << 1, x^26688 mod p(x)` << 1 */ + { 0x00000001dbc672be, 0x00000001a8da60c6 }, + /* x^25600 mod p(x)` << 1, x^25664 mod p(x)` << 1 */ + { 0x00000000b04d77f6, 0x000000013cf63820 }, + /* x^24576 mod p(x)` << 1, x^24640 mod p(x)` << 1 */ + { 0x0000000124400d96, 0x00000000bec12e1e }, + /* x^23552 mod p(x)` << 1, x^23616 mod p(x)` << 1 */ + { 0x000000014ca4b414, 0x00000001c6368010 }, + /* x^22528 mod p(x)` << 1, x^22592 mod p(x)` << 1 */ + { 0x000000012fe2c938, 0x00000001e6e78758 }, + /* x^21504 mod p(x)` << 1, x^21568 mod p(x)` << 1 */ + { 0x00000001faed01e6, 0x000000008d7f2b3c }, + /* x^20480 mod p(x)` << 1, x^20544 mod p(x)` << 1 */ + { 0x000000007e80ecfe, 0x000000016b4a156e }, + /* x^19456 mod p(x)` << 1, x^19520 mod p(x)` << 1 */ + { 0x0000000098daee94, 0x00000001c63cfeb6 }, + /* x^18432 mod p(x)` << 1, x^18496 mod p(x)` << 1 */ + { 0x000000010a04edea, 0x000000015f902670 }, + /* x^17408 mod p(x)` << 1, x^17472 mod p(x)` << 1 */ + { 0x00000001c00b4524, 0x00000001cd5de11e }, + /* x^16384 mod p(x)` << 1, x^16448 mod p(x)` << 1 */ + { 0x0000000170296550, 0x000000001acaec54 }, + /* x^15360 mod p(x)` << 1, x^15424 mod p(x)` << 1 */ + { 0x0000000181afaa48, 0x000000002bd0ca78 }, + /* x^14336 mod p(x)` << 1, x^14400 mod p(x)` << 1 */ + { 0x0000000185a31ffa, 0x0000000032d63d5c }, + /* x^13312 mod p(x)` << 1, x^13376 mod p(x)` << 1 */ + { 0x000000002469f608, 0x000000001c6d4e4c }, + /* x^12288 mod p(x)` << 1, x^12352 mod p(x)` << 1 */ + { 0x000000006980102a, 0x0000000106a60b92 }, + /* x^11264 mod p(x)` << 1, x^11328 mod p(x)` << 1 */ + { 0x0000000111ea9ca8, 0x00000000d3855e12 }, + /* x^10240 mod p(x)` << 1, x^10304 mod p(x)` << 1 */ + { 0x00000001bd1d29ce, 0x00000000e3125636 }, + /* x^9216 mod p(x)` << 1, x^9280 mod p(x)` << 1 */ + { 0x00000001b34b9580, 0x000000009e8f7ea4 }, + /* x^8192 mod p(x)` << 1, x^8256 mod p(x)` << 1 */ + { 0x000000003076054e, 0x00000001c82e562c }, + /* x^7168 mod p(x)` << 1, x^7232 mod p(x)` << 1 */ + { 0x000000012a608ea4, 0x00000000ca9f09ce }, + /* x^6144 mod p(x)` << 1, x^6208 mod p(x)` << 1 */ + { 0x00000000784d05fe, 0x00000000c63764e6 }, + /* x^5120 mod p(x)` << 1, x^5184 mod p(x)` << 1 */ + { 0x000000016ef0d82a, 0x0000000168d2e49e }, + /* x^4096 mod p(x)` << 1, x^4160 mod p(x)` << 1 */ + { 0x0000000075bda454, 0x00000000e986c148 }, + /* x^3072 mod p(x)` << 1, x^3136 mod p(x)` << 1 */ + { 0x000000003dc0a1c4, 0x00000000cfb65894 }, + /* x^2048 mod p(x)` << 1, x^2112 mod p(x)` << 1 */ + { 0x00000000e9a5d8be, 0x0000000111cadee4 }, + /* x^1024 mod p(x)` << 1, x^1088 mod p(x)` << 1 */ + { 0x00000001609bc4b4, 0x0000000171fb63ce } +#else /* __LITTLE_ENDIAN__ */ + /* x^261120 mod p(x)` << 1, x^261184 mod p(x)` << 1 */ + { 0x00000000b6ca9e20, 0x000000009c37c408 }, + /* x^260096 mod p(x)` << 1, x^260160 mod p(x)` << 1 */ + { 0x00000000350249a8, 0x00000001b51df26c }, + /* x^259072 mod p(x)` << 1, x^259136 mod p(x)` << 1 */ + { 0x00000001862dac54, 0x000000000724b9d0 }, + /* x^258048 mod p(x)` << 1, x^258112 mod p(x)` << 1 */ + { 0x00000001d87fb48c, 0x00000001c00532fe }, + /* x^257024 mod p(x)` << 1, x^257088 mod p(x)` << 1 */ + { 0x00000001f39b699e, 0x00000000f05a9362 }, + /* x^256000 mod p(x)` << 1, x^256064 mod p(x)` << 1 */ + { 0x0000000101da11b4, 0x00000001e1007970 }, + /* x^254976 mod p(x)` << 1, x^255040 mod p(x)` << 1 */ + { 0x00000001cab571e0, 0x00000000a57366ee }, + /* x^253952 mod p(x)` << 1, x^254016 mod p(x)` << 1 */ + { 0x00000000c7020cfe, 0x0000000192011284 }, + /* x^252928 mod p(x)` << 1, x^252992 mod p(x)` << 1 */ + { 0x00000000cdaed1ae, 0x0000000162716d9a }, + /* x^251904 mod p(x)` << 1, x^251968 mod p(x)` << 1 */ + { 0x00000001e804effc, 0x00000000cd97ecde }, + /* x^250880 mod p(x)` << 1, x^250944 mod p(x)` << 1 */ + { 0x0000000077c3ea3a, 0x0000000058812bc0 }, + /* x^249856 mod p(x)` << 1, x^249920 mod p(x)` << 1 */ + { 0x0000000068df31b4, 0x0000000088b8c12e }, + /* x^248832 mod p(x)` << 1, x^248896 mod p(x)` << 1 */ + { 0x00000000b059b6c2, 0x00000001230b234c }, + /* x^247808 mod p(x)` << 1, x^247872 mod p(x)` << 1 */ + { 0x0000000145fb8ed8, 0x00000001120b416e }, + /* x^246784 mod p(x)` << 1, x^246848 mod p(x)` << 1 */ + { 0x00000000cbc09168, 0x00000001974aecb0 }, + /* x^245760 mod p(x)` << 1, x^245824 mod p(x)` << 1 */ + { 0x000000005ceeedc2, 0x000000008ee3f226 }, + /* x^244736 mod p(x)` << 1, x^244800 mod p(x)` << 1 */ + { 0x0000000047d74e86, 0x00000001089aba9a }, + /* x^243712 mod p(x)` << 1, x^243776 mod p(x)` << 1 */ + { 0x00000001407e9e22, 0x0000000065113872 }, + /* x^242688 mod p(x)` << 1, x^242752 mod p(x)` << 1 */ + { 0x00000001da967bda, 0x000000005c07ec10 }, + /* x^241664 mod p(x)` << 1, x^241728 mod p(x)` << 1 */ + { 0x000000006c898368, 0x0000000187590924 }, + /* x^240640 mod p(x)` << 1, x^240704 mod p(x)` << 1 */ + { 0x00000000f2d14c98, 0x00000000e35da7c6 }, + /* x^239616 mod p(x)` << 1, x^239680 mod p(x)` << 1 */ + { 0x00000001993c6ad4, 0x000000000415855a }, + /* x^238592 mod p(x)` << 1, x^238656 mod p(x)` << 1 */ + { 0x000000014683d1ac, 0x0000000073617758 }, + /* x^237568 mod p(x)` << 1, x^237632 mod p(x)` << 1 */ + { 0x00000001a7c93e6c, 0x0000000176021d28 }, + /* x^236544 mod p(x)` << 1, x^236608 mod p(x)` << 1 */ + { 0x000000010211e90a, 0x00000001c358fd0a }, + /* x^235520 mod p(x)` << 1, x^235584 mod p(x)` << 1 */ + { 0x000000001119403e, 0x00000001ff7a2c18 }, + /* x^234496 mod p(x)` << 1, x^234560 mod p(x)` << 1 */ + { 0x000000001c3261aa, 0x00000000f2d9f7e4 }, + /* x^233472 mod p(x)` << 1, x^233536 mod p(x)` << 1 */ + { 0x000000014e37a634, 0x000000016cf1f9c8 }, + /* x^232448 mod p(x)` << 1, x^232512 mod p(x)` << 1 */ + { 0x0000000073786c0c, 0x000000010af9279a }, + /* x^231424 mod p(x)` << 1, x^231488 mod p(x)` << 1 */ + { 0x000000011dc037f8, 0x0000000004f101e8 }, + /* x^230400 mod p(x)` << 1, x^230464 mod p(x)` << 1 */ + { 0x0000000031433dfc, 0x0000000070bcf184 }, + /* x^229376 mod p(x)` << 1, x^229440 mod p(x)` << 1 */ + { 0x000000009cde8348, 0x000000000a8de642 }, + /* x^228352 mod p(x)` << 1, x^228416 mod p(x)` << 1 */ + { 0x0000000038d3c2a6, 0x0000000062ea130c }, + /* x^227328 mod p(x)` << 1, x^227392 mod p(x)` << 1 */ + { 0x000000011b25f260, 0x00000001eb31cbb2 }, + /* x^226304 mod p(x)` << 1, x^226368 mod p(x)` << 1 */ + { 0x000000001629e6f0, 0x0000000170783448 }, + /* x^225280 mod p(x)` << 1, x^225344 mod p(x)` << 1 */ + { 0x0000000160838b4c, 0x00000001a684b4c6 }, + /* x^224256 mod p(x)` << 1, x^224320 mod p(x)` << 1 */ + { 0x000000007a44011c, 0x00000000253ca5b4 }, + /* x^223232 mod p(x)` << 1, x^223296 mod p(x)` << 1 */ + { 0x00000000226f417a, 0x0000000057b4b1e2 }, + /* x^222208 mod p(x)` << 1, x^222272 mod p(x)` << 1 */ + { 0x0000000045eb2eb4, 0x00000000b6bd084c }, + /* x^221184 mod p(x)` << 1, x^221248 mod p(x)` << 1 */ + { 0x000000014459d70c, 0x0000000123c2d592 }, + /* x^220160 mod p(x)` << 1, x^220224 mod p(x)` << 1 */ + { 0x00000001d406ed82, 0x00000000159dafce }, + /* x^219136 mod p(x)` << 1, x^219200 mod p(x)` << 1 */ + { 0x0000000160c8e1a8, 0x0000000127e1a64e }, + /* x^218112 mod p(x)` << 1, x^218176 mod p(x)` << 1 */ + { 0x0000000027ba8098, 0x0000000056860754 }, + /* x^217088 mod p(x)` << 1, x^217152 mod p(x)` << 1 */ + { 0x000000006d92d018, 0x00000001e661aae8 }, + /* x^216064 mod p(x)` << 1, x^216128 mod p(x)` << 1 */ + { 0x000000012ed7e3f2, 0x00000000f82c6166 }, + /* x^215040 mod p(x)` << 1, x^215104 mod p(x)` << 1 */ + { 0x000000002dc87788, 0x00000000c4f9c7ae }, + /* x^214016 mod p(x)` << 1, x^214080 mod p(x)` << 1 */ + { 0x0000000018240bb8, 0x0000000074203d20 }, + /* x^212992 mod p(x)` << 1, x^213056 mod p(x)` << 1 */ + { 0x000000001ad38158, 0x0000000198173052 }, + /* x^211968 mod p(x)` << 1, x^212032 mod p(x)` << 1 */ + { 0x00000001396b78f2, 0x00000001ce8aba54 }, + /* x^210944 mod p(x)` << 1, x^211008 mod p(x)` << 1 */ + { 0x000000011a681334, 0x00000001850d5d94 }, + /* x^209920 mod p(x)` << 1, x^209984 mod p(x)` << 1 */ + { 0x000000012104732e, 0x00000001d609239c }, + /* x^208896 mod p(x)` << 1, x^208960 mod p(x)` << 1 */ + { 0x00000000a140d90c, 0x000000001595f048 }, + /* x^207872 mod p(x)` << 1, x^207936 mod p(x)` << 1 */ + { 0x00000001b7215eda, 0x0000000042ccee08 }, + /* x^206848 mod p(x)` << 1, x^206912 mod p(x)` << 1 */ + { 0x00000001aaf1df3c, 0x000000010a389d74 }, + /* x^205824 mod p(x)` << 1, x^205888 mod p(x)` << 1 */ + { 0x0000000029d15b8a, 0x000000012a840da6 }, + /* x^204800 mod p(x)` << 1, x^204864 mod p(x)` << 1 */ + { 0x00000000f1a96922, 0x000000001d181c0c }, + /* x^203776 mod p(x)` << 1, x^203840 mod p(x)` << 1 */ + { 0x00000001ac80d03c, 0x0000000068b7d1f6 }, + /* x^202752 mod p(x)` << 1, x^202816 mod p(x)` << 1 */ + { 0x000000000f11d56a, 0x000000005b0f14fc }, + /* x^201728 mod p(x)` << 1, x^201792 mod p(x)` << 1 */ + { 0x00000001f1c022a2, 0x0000000179e9e730 }, + /* x^200704 mod p(x)` << 1, x^200768 mod p(x)` << 1 */ + { 0x0000000173d00ae2, 0x00000001ce1368d6 }, + /* x^199680 mod p(x)` << 1, x^199744 mod p(x)` << 1 */ + { 0x00000001d4ffe4ac, 0x0000000112c3a84c }, + /* x^198656 mod p(x)` << 1, x^198720 mod p(x)` << 1 */ + { 0x000000016edc5ae4, 0x00000000de940fee }, + /* x^197632 mod p(x)` << 1, x^197696 mod p(x)` << 1 */ + { 0x00000001f1a02140, 0x00000000fe896b7e }, + /* x^196608 mod p(x)` << 1, x^196672 mod p(x)` << 1 */ + { 0x00000000ca0b28a0, 0x00000001f797431c }, + /* x^195584 mod p(x)` << 1, x^195648 mod p(x)` << 1 */ + { 0x00000001928e30a2, 0x0000000053e989ba }, + /* x^194560 mod p(x)` << 1, x^194624 mod p(x)` << 1 */ + { 0x0000000097b1b002, 0x000000003920cd16 }, + /* x^193536 mod p(x)` << 1, x^193600 mod p(x)` << 1 */ + { 0x00000000b15bf906, 0x00000001e6f579b8 }, + /* x^192512 mod p(x)` << 1, x^192576 mod p(x)` << 1 */ + { 0x00000000411c5d52, 0x000000007493cb0a }, + /* x^191488 mod p(x)` << 1, x^191552 mod p(x)` << 1 */ + { 0x00000001c36f3300, 0x00000001bdd376d8 }, + /* x^190464 mod p(x)` << 1, x^190528 mod p(x)` << 1 */ + { 0x00000001119227e0, 0x000000016badfee6 }, + /* x^189440 mod p(x)` << 1, x^189504 mod p(x)` << 1 */ + { 0x00000000114d4702, 0x0000000071de5c58 }, + /* x^188416 mod p(x)` << 1, x^188480 mod p(x)` << 1 */ + { 0x00000000458b5b98, 0x00000000453f317c }, + /* x^187392 mod p(x)` << 1, x^187456 mod p(x)` << 1 */ + { 0x000000012e31fb8e, 0x0000000121675cce }, + /* x^186368 mod p(x)` << 1, x^186432 mod p(x)` << 1 */ + { 0x000000005cf619d8, 0x00000001f409ee92 }, + /* x^185344 mod p(x)` << 1, x^185408 mod p(x)` << 1 */ + { 0x0000000063f4d8b2, 0x00000000f36b9c88 }, + /* x^184320 mod p(x)` << 1, x^184384 mod p(x)` << 1 */ + { 0x000000004138dc8a, 0x0000000036b398f4 }, + /* x^183296 mod p(x)` << 1, x^183360 mod p(x)` << 1 */ + { 0x00000001d29ee8e0, 0x00000001748f9adc }, + /* x^182272 mod p(x)` << 1, x^182336 mod p(x)` << 1 */ + { 0x000000006a08ace8, 0x00000001be94ec00 }, + /* x^181248 mod p(x)` << 1, x^181312 mod p(x)` << 1 */ + { 0x0000000127d42010, 0x00000000b74370d6 }, + /* x^180224 mod p(x)` << 1, x^180288 mod p(x)` << 1 */ + { 0x0000000019d76b62, 0x00000001174d0b98 }, + /* x^179200 mod p(x)` << 1, x^179264 mod p(x)` << 1 */ + { 0x00000001b1471f6e, 0x00000000befc06a4 }, + /* x^178176 mod p(x)` << 1, x^178240 mod p(x)` << 1 */ + { 0x00000001f64c19cc, 0x00000001ae125288 }, + /* x^177152 mod p(x)` << 1, x^177216 mod p(x)` << 1 */ + { 0x00000000003c0ea0, 0x0000000095c19b34 }, + /* x^176128 mod p(x)` << 1, x^176192 mod p(x)` << 1 */ + { 0x000000014d73abf6, 0x00000001a78496f2 }, + /* x^175104 mod p(x)` << 1, x^175168 mod p(x)` << 1 */ + { 0x00000001620eb844, 0x00000001ac5390a0 }, + /* x^174080 mod p(x)` << 1, x^174144 mod p(x)` << 1 */ + { 0x0000000147655048, 0x000000002a80ed6e }, + /* x^173056 mod p(x)` << 1, x^173120 mod p(x)` << 1 */ + { 0x0000000067b5077e, 0x00000001fa9b0128 }, + /* x^172032 mod p(x)` << 1, x^172096 mod p(x)` << 1 */ + { 0x0000000010ffe206, 0x00000001ea94929e }, + /* x^171008 mod p(x)` << 1, x^171072 mod p(x)` << 1 */ + { 0x000000000fee8f1e, 0x0000000125f4305c }, + /* x^169984 mod p(x)` << 1, x^170048 mod p(x)` << 1 */ + { 0x00000001da26fbae, 0x00000001471e2002 }, + /* x^168960 mod p(x)` << 1, x^169024 mod p(x)` << 1 */ + { 0x00000001b3a8bd88, 0x0000000132d2253a }, + /* x^167936 mod p(x)` << 1, x^168000 mod p(x)` << 1 */ + { 0x00000000e8f3898e, 0x00000000f26b3592 }, + /* x^166912 mod p(x)` << 1, x^166976 mod p(x)` << 1 */ + { 0x00000000b0d0d28c, 0x00000000bc8b67b0 }, + /* x^165888 mod p(x)` << 1, x^165952 mod p(x)` << 1 */ + { 0x0000000030f2a798, 0x000000013a826ef2 }, + /* x^164864 mod p(x)` << 1, x^164928 mod p(x)` << 1 */ + { 0x000000000fba1002, 0x0000000081482c84 }, + /* x^163840 mod p(x)` << 1, x^163904 mod p(x)` << 1 */ + { 0x00000000bdb9bd72, 0x00000000e77307c2 }, + /* x^162816 mod p(x)` << 1, x^162880 mod p(x)` << 1 */ + { 0x0000000075d3bf5a, 0x00000000d4a07ec8 }, + /* x^161792 mod p(x)` << 1, x^161856 mod p(x)` << 1 */ + { 0x00000000ef1f98a0, 0x0000000017102100 }, + /* x^160768 mod p(x)` << 1, x^160832 mod p(x)` << 1 */ + { 0x00000000689c7602, 0x00000000db406486 }, + /* x^159744 mod p(x)` << 1, x^159808 mod p(x)` << 1 */ + { 0x000000016d5fa5fe, 0x0000000192db7f88 }, + /* x^158720 mod p(x)` << 1, x^158784 mod p(x)` << 1 */ + { 0x00000001d0d2b9ca, 0x000000018bf67b1e }, + /* x^157696 mod p(x)` << 1, x^157760 mod p(x)` << 1 */ + { 0x0000000041e7b470, 0x000000007c09163e }, + /* x^156672 mod p(x)` << 1, x^156736 mod p(x)` << 1 */ + { 0x00000001cbb6495e, 0x000000000adac060 }, + /* x^155648 mod p(x)` << 1, x^155712 mod p(x)` << 1 */ + { 0x000000010052a0b0, 0x00000000bd8316ae }, + /* x^154624 mod p(x)` << 1, x^154688 mod p(x)` << 1 */ + { 0x00000001d8effb5c, 0x000000019f09ab54 }, + /* x^153600 mod p(x)` << 1, x^153664 mod p(x)` << 1 */ + { 0x00000001d969853c, 0x0000000125155542 }, + /* x^152576 mod p(x)` << 1, x^152640 mod p(x)` << 1 */ + { 0x00000000523ccce2, 0x000000018fdb5882 }, + /* x^151552 mod p(x)` << 1, x^151616 mod p(x)` << 1 */ + { 0x000000001e2436bc, 0x00000000e794b3f4 }, + /* x^150528 mod p(x)` << 1, x^150592 mod p(x)` << 1 */ + { 0x00000000ddd1c3a2, 0x000000016f9bb022 }, + /* x^149504 mod p(x)` << 1, x^149568 mod p(x)` << 1 */ + { 0x0000000019fcfe38, 0x00000000290c9978 }, + /* x^148480 mod p(x)` << 1, x^148544 mod p(x)` << 1 */ + { 0x00000001ce95db64, 0x0000000083c0f350 }, + /* x^147456 mod p(x)` << 1, x^147520 mod p(x)` << 1 */ + { 0x00000000af582806, 0x0000000173ea6628 }, + /* x^146432 mod p(x)` << 1, x^146496 mod p(x)` << 1 */ + { 0x00000001006388f6, 0x00000001c8b4e00a }, + /* x^145408 mod p(x)` << 1, x^145472 mod p(x)` << 1 */ + { 0x0000000179eca00a, 0x00000000de95d6aa }, + /* x^144384 mod p(x)` << 1, x^144448 mod p(x)` << 1 */ + { 0x0000000122410a6a, 0x000000010b7f7248 }, + /* x^143360 mod p(x)` << 1, x^143424 mod p(x)` << 1 */ + { 0x000000004288e87c, 0x00000001326e3a06 }, + /* x^142336 mod p(x)` << 1, x^142400 mod p(x)` << 1 */ + { 0x000000016c5490da, 0x00000000bb62c2e6 }, + /* x^141312 mod p(x)` << 1, x^141376 mod p(x)` << 1 */ + { 0x00000000d1c71f6e, 0x0000000156a4b2c2 }, + /* x^140288 mod p(x)` << 1, x^140352 mod p(x)` << 1 */ + { 0x00000001b4ce08a6, 0x000000011dfe763a }, + /* x^139264 mod p(x)` << 1, x^139328 mod p(x)` << 1 */ + { 0x00000001466ba60c, 0x000000007bcca8e2 }, + /* x^138240 mod p(x)` << 1, x^138304 mod p(x)` << 1 */ + { 0x00000001f6c488a4, 0x0000000186118faa }, + /* x^137216 mod p(x)` << 1, x^137280 mod p(x)` << 1 */ + { 0x000000013bfb0682, 0x0000000111a65a88 }, + /* x^136192 mod p(x)` << 1, x^136256 mod p(x)` << 1 */ + { 0x00000000690e9e54, 0x000000003565e1c4 }, + /* x^135168 mod p(x)` << 1, x^135232 mod p(x)` << 1 */ + { 0x00000000281346b6, 0x000000012ed02a82 }, + /* x^134144 mod p(x)` << 1, x^134208 mod p(x)` << 1 */ + { 0x0000000156464024, 0x00000000c486ecfc }, + /* x^133120 mod p(x)` << 1, x^133184 mod p(x)` << 1 */ + { 0x000000016063a8dc, 0x0000000001b951b2 }, + /* x^132096 mod p(x)` << 1, x^132160 mod p(x)` << 1 */ + { 0x0000000116a66362, 0x0000000048143916 }, + /* x^131072 mod p(x)` << 1, x^131136 mod p(x)` << 1 */ + { 0x000000017e8aa4d2, 0x00000001dc2ae124 }, + /* x^130048 mod p(x)` << 1, x^130112 mod p(x)` << 1 */ + { 0x00000001728eb10c, 0x00000001416c58d6 }, + /* x^129024 mod p(x)` << 1, x^129088 mod p(x)` << 1 */ + { 0x00000001b08fd7fa, 0x00000000a479744a }, + /* x^128000 mod p(x)` << 1, x^128064 mod p(x)` << 1 */ + { 0x00000001092a16e8, 0x0000000096ca3a26 }, + /* x^126976 mod p(x)` << 1, x^127040 mod p(x)` << 1 */ + { 0x00000000a505637c, 0x00000000ff223d4e }, + /* x^125952 mod p(x)` << 1, x^126016 mod p(x)` << 1 */ + { 0x00000000d94869b2, 0x000000010e84da42 }, + /* x^124928 mod p(x)` << 1, x^124992 mod p(x)` << 1 */ + { 0x00000001c8b203ae, 0x00000001b61ba3d0 }, + /* x^123904 mod p(x)` << 1, x^123968 mod p(x)` << 1 */ + { 0x000000005704aea0, 0x00000000680f2de8 }, + /* x^122880 mod p(x)` << 1, x^122944 mod p(x)` << 1 */ + { 0x000000012e295fa2, 0x000000008772a9a8 }, + /* x^121856 mod p(x)` << 1, x^121920 mod p(x)` << 1 */ + { 0x000000011d0908bc, 0x0000000155f295bc }, + /* x^120832 mod p(x)` << 1, x^120896 mod p(x)` << 1 */ + { 0x0000000193ed97ea, 0x00000000595f9282 }, + /* x^119808 mod p(x)` << 1, x^119872 mod p(x)` << 1 */ + { 0x000000013a0f1c52, 0x0000000164b1c25a }, + /* x^118784 mod p(x)` << 1, x^118848 mod p(x)` << 1 */ + { 0x000000010c2c40c0, 0x00000000fbd67c50 }, + /* x^117760 mod p(x)` << 1, x^117824 mod p(x)` << 1 */ + { 0x00000000ff6fac3e, 0x0000000096076268 }, + /* x^116736 mod p(x)` << 1, x^116800 mod p(x)` << 1 */ + { 0x000000017b3609c0, 0x00000001d288e4cc }, + /* x^115712 mod p(x)` << 1, x^115776 mod p(x)` << 1 */ + { 0x0000000088c8c922, 0x00000001eaac1bdc }, + /* x^114688 mod p(x)` << 1, x^114752 mod p(x)` << 1 */ + { 0x00000001751baae6, 0x00000001f1ea39e2 }, + /* x^113664 mod p(x)` << 1, x^113728 mod p(x)` << 1 */ + { 0x0000000107952972, 0x00000001eb6506fc }, + /* x^112640 mod p(x)` << 1, x^112704 mod p(x)` << 1 */ + { 0x0000000162b00abe, 0x000000010f806ffe }, + /* x^111616 mod p(x)` << 1, x^111680 mod p(x)` << 1 */ + { 0x000000000d7b404c, 0x000000010408481e }, + /* x^110592 mod p(x)` << 1, x^110656 mod p(x)` << 1 */ + { 0x00000000763b13d4, 0x0000000188260534 }, + /* x^109568 mod p(x)` << 1, x^109632 mod p(x)` << 1 */ + { 0x00000000f6dc22d8, 0x0000000058fc73e0 }, + /* x^108544 mod p(x)` << 1, x^108608 mod p(x)` << 1 */ + { 0x000000007daae060, 0x00000000391c59b8 }, + /* x^107520 mod p(x)` << 1, x^107584 mod p(x)` << 1 */ + { 0x000000013359ab7c, 0x000000018b638400 }, + /* x^106496 mod p(x)` << 1, x^106560 mod p(x)` << 1 */ + { 0x000000008add438a, 0x000000011738f5c4 }, + /* x^105472 mod p(x)` << 1, x^105536 mod p(x)` << 1 */ + { 0x00000001edbefdea, 0x000000008cf7c6da }, + /* x^104448 mod p(x)` << 1, x^104512 mod p(x)` << 1 */ + { 0x000000004104e0f8, 0x00000001ef97fb16 }, + /* x^103424 mod p(x)` << 1, x^103488 mod p(x)` << 1 */ + { 0x00000000b48a8222, 0x0000000102130e20 }, + /* x^102400 mod p(x)` << 1, x^102464 mod p(x)` << 1 */ + { 0x00000001bcb46844, 0x00000000db968898 }, + /* x^101376 mod p(x)` << 1, x^101440 mod p(x)` << 1 */ + { 0x000000013293ce0a, 0x00000000b5047b5e }, + /* x^100352 mod p(x)` << 1, x^100416 mod p(x)` << 1 */ + { 0x00000001710d0844, 0x000000010b90fdb2 }, + /* x^99328 mod p(x)` << 1, x^99392 mod p(x)` << 1 */ + { 0x0000000117907f6e, 0x000000004834a32e }, + /* x^98304 mod p(x)` << 1, x^98368 mod p(x)` << 1 */ + { 0x0000000087ddf93e, 0x0000000059c8f2b0 }, + /* x^97280 mod p(x)` << 1, x^97344 mod p(x)` << 1 */ + { 0x000000005970e9b0, 0x0000000122cec508 }, + /* x^96256 mod p(x)` << 1, x^96320 mod p(x)` << 1 */ + { 0x0000000185b2b7d0, 0x000000000a330cda }, + /* x^95232 mod p(x)` << 1, x^95296 mod p(x)` << 1 */ + { 0x00000001dcee0efc, 0x000000014a47148c }, + /* x^94208 mod p(x)` << 1, x^94272 mod p(x)` << 1 */ + { 0x0000000030da2722, 0x0000000042c61cb8 }, + /* x^93184 mod p(x)` << 1, x^93248 mod p(x)` << 1 */ + { 0x000000012f925a18, 0x0000000012fe6960 }, + /* x^92160 mod p(x)` << 1, x^92224 mod p(x)` << 1 */ + { 0x00000000dd2e357c, 0x00000000dbda2c20 }, + /* x^91136 mod p(x)` << 1, x^91200 mod p(x)` << 1 */ + { 0x00000000071c80de, 0x000000011122410c }, + /* x^90112 mod p(x)` << 1, x^90176 mod p(x)` << 1 */ + { 0x000000011513140a, 0x00000000977b2070 }, + /* x^89088 mod p(x)` << 1, x^89152 mod p(x)` << 1 */ + { 0x00000001df876e8e, 0x000000014050438e }, + /* x^88064 mod p(x)` << 1, x^88128 mod p(x)` << 1 */ + { 0x000000015f81d6ce, 0x0000000147c840e8 }, + /* x^87040 mod p(x)` << 1, x^87104 mod p(x)` << 1 */ + { 0x000000019dd94dbe, 0x00000001cc7c88ce }, + /* x^86016 mod p(x)` << 1, x^86080 mod p(x)` << 1 */ + { 0x00000001373d206e, 0x00000001476b35a4 }, + /* x^84992 mod p(x)` << 1, x^85056 mod p(x)` << 1 */ + { 0x00000000668ccade, 0x000000013d52d508 }, + /* x^83968 mod p(x)` << 1, x^84032 mod p(x)` << 1 */ + { 0x00000001b192d268, 0x000000008e4be32e }, + /* x^82944 mod p(x)` << 1, x^83008 mod p(x)` << 1 */ + { 0x00000000e30f3a78, 0x00000000024120fe }, + /* x^81920 mod p(x)` << 1, x^81984 mod p(x)` << 1 */ + { 0x000000010ef1f7bc, 0x00000000ddecddb4 }, + /* x^80896 mod p(x)` << 1, x^80960 mod p(x)` << 1 */ + { 0x00000001f5ac7380, 0x00000000d4d403bc }, + /* x^79872 mod p(x)` << 1, x^79936 mod p(x)` << 1 */ + { 0x000000011822ea70, 0x00000001734b89aa }, + /* x^78848 mod p(x)` << 1, x^78912 mod p(x)` << 1 */ + { 0x00000000c3a33848, 0x000000010e7a58d6 }, + /* x^77824 mod p(x)` << 1, x^77888 mod p(x)` << 1 */ + { 0x00000001bd151c24, 0x00000001f9f04e9c }, + /* x^76800 mod p(x)` << 1, x^76864 mod p(x)` << 1 */ + { 0x0000000056002d76, 0x00000000b692225e }, + /* x^75776 mod p(x)` << 1, x^75840 mod p(x)` << 1 */ + { 0x000000014657c4f4, 0x000000019b8d3f3e }, + /* x^74752 mod p(x)` << 1, x^74816 mod p(x)` << 1 */ + { 0x0000000113742d7c, 0x00000001a874f11e }, + /* x^73728 mod p(x)` << 1, x^73792 mod p(x)` << 1 */ + { 0x000000019c5920ba, 0x000000010d5a4254 }, + /* x^72704 mod p(x)` << 1, x^72768 mod p(x)` << 1 */ + { 0x000000005216d2d6, 0x00000000bbb2f5d6 }, + /* x^71680 mod p(x)` << 1, x^71744 mod p(x)` << 1 */ + { 0x0000000136f5ad8a, 0x0000000179cc0e36 }, + /* x^70656 mod p(x)` << 1, x^70720 mod p(x)` << 1 */ + { 0x000000018b07beb6, 0x00000001dca1da4a }, + /* x^69632 mod p(x)` << 1, x^69696 mod p(x)` << 1 */ + { 0x00000000db1e93b0, 0x00000000feb1a192 }, + /* x^68608 mod p(x)` << 1, x^68672 mod p(x)` << 1 */ + { 0x000000000b96fa3a, 0x00000000d1eeedd6 }, + /* x^67584 mod p(x)` << 1, x^67648 mod p(x)` << 1 */ + { 0x00000001d9968af0, 0x000000008fad9bb4 }, + /* x^66560 mod p(x)` << 1, x^66624 mod p(x)` << 1 */ + { 0x000000000e4a77a2, 0x00000001884938e4 }, + /* x^65536 mod p(x)` << 1, x^65600 mod p(x)` << 1 */ + { 0x00000000508c2ac8, 0x00000001bc2e9bc0 }, + /* x^64512 mod p(x)` << 1, x^64576 mod p(x)` << 1 */ + { 0x0000000021572a80, 0x00000001f9658a68 }, + /* x^63488 mod p(x)` << 1, x^63552 mod p(x)` << 1 */ + { 0x00000001b859daf2, 0x000000001b9224fc }, + /* x^62464 mod p(x)` << 1, x^62528 mod p(x)` << 1 */ + { 0x000000016f788474, 0x0000000055b2fb84 }, + /* x^61440 mod p(x)` << 1, x^61504 mod p(x)` << 1 */ + { 0x00000001b438810e, 0x000000018b090348 }, + /* x^60416 mod p(x)` << 1, x^60480 mod p(x)` << 1 */ + { 0x0000000095ddc6f2, 0x000000011ccbd5ea }, + /* x^59392 mod p(x)` << 1, x^59456 mod p(x)` << 1 */ + { 0x00000001d977c20c, 0x0000000007ae47f8 }, + /* x^58368 mod p(x)` << 1, x^58432 mod p(x)` << 1 */ + { 0x00000000ebedb99a, 0x0000000172acbec0 }, + /* x^57344 mod p(x)` << 1, x^57408 mod p(x)` << 1 */ + { 0x00000001df9e9e92, 0x00000001c6e3ff20 }, + /* x^56320 mod p(x)` << 1, x^56384 mod p(x)` << 1 */ + { 0x00000001a4a3f952, 0x00000000e1b38744 }, + /* x^55296 mod p(x)` << 1, x^55360 mod p(x)` << 1 */ + { 0x00000000e2f51220, 0x00000000791585b2 }, + /* x^54272 mod p(x)` << 1, x^54336 mod p(x)` << 1 */ + { 0x000000004aa01f3e, 0x00000000ac53b894 }, + /* x^53248 mod p(x)` << 1, x^53312 mod p(x)` << 1 */ + { 0x00000000b3e90a58, 0x00000001ed5f2cf4 }, + /* x^52224 mod p(x)` << 1, x^52288 mod p(x)` << 1 */ + { 0x000000000c9ca2aa, 0x00000001df48b2e0 }, + /* x^51200 mod p(x)` << 1, x^51264 mod p(x)` << 1 */ + { 0x0000000151682316, 0x00000000049c1c62 }, + /* x^50176 mod p(x)` << 1, x^50240 mod p(x)` << 1 */ + { 0x0000000036fce78c, 0x000000017c460c12 }, + /* x^49152 mod p(x)` << 1, x^49216 mod p(x)` << 1 */ + { 0x000000009037dc10, 0x000000015be4da7e }, + /* x^48128 mod p(x)` << 1, x^48192 mod p(x)` << 1 */ + { 0x00000000d3298582, 0x000000010f38f668 }, + /* x^47104 mod p(x)` << 1, x^47168 mod p(x)` << 1 */ + { 0x00000001b42e8ad6, 0x0000000039f40a00 }, + /* x^46080 mod p(x)` << 1, x^46144 mod p(x)` << 1 */ + { 0x00000000142a9838, 0x00000000bd4c10c4 }, + /* x^45056 mod p(x)` << 1, x^45120 mod p(x)` << 1 */ + { 0x0000000109c7f190, 0x0000000042db1d98 }, + /* x^44032 mod p(x)` << 1, x^44096 mod p(x)` << 1 */ + { 0x0000000056ff9310, 0x00000001c905bae6 }, + /* x^43008 mod p(x)` << 1, x^43072 mod p(x)` << 1 */ + { 0x00000001594513aa, 0x00000000069d40ea }, + /* x^41984 mod p(x)` << 1, x^42048 mod p(x)` << 1 */ + { 0x00000001e3b5b1e8, 0x000000008e4fbad0 }, + /* x^40960 mod p(x)` << 1, x^41024 mod p(x)` << 1 */ + { 0x000000011dd5fc08, 0x0000000047bedd46 }, + /* x^39936 mod p(x)` << 1, x^40000 mod p(x)` << 1 */ + { 0x00000001675f0cc2, 0x0000000026396bf8 }, + /* x^38912 mod p(x)` << 1, x^38976 mod p(x)` << 1 */ + { 0x00000000d1c8dd44, 0x00000000379beb92 }, + /* x^37888 mod p(x)` << 1, x^37952 mod p(x)` << 1 */ + { 0x0000000115ebd3d8, 0x000000000abae54a }, + /* x^36864 mod p(x)` << 1, x^36928 mod p(x)` << 1 */ + { 0x00000001ecbd0dac, 0x0000000007e6a128 }, + /* x^35840 mod p(x)` << 1, x^35904 mod p(x)` << 1 */ + { 0x00000000cdf67af2, 0x000000000ade29d2 }, + /* x^34816 mod p(x)` << 1, x^34880 mod p(x)` << 1 */ + { 0x000000004c01ff4c, 0x00000000f974c45c }, + /* x^33792 mod p(x)` << 1, x^33856 mod p(x)` << 1 */ + { 0x00000000f2d8657e, 0x00000000e77ac60a }, + /* x^32768 mod p(x)` << 1, x^32832 mod p(x)` << 1 */ + { 0x000000006bae74c4, 0x0000000145895816 }, + /* x^31744 mod p(x)` << 1, x^31808 mod p(x)` << 1 */ + { 0x0000000152af8aa0, 0x0000000038e362be }, + /* x^30720 mod p(x)` << 1, x^30784 mod p(x)` << 1 */ + { 0x0000000004663802, 0x000000007f991a64 }, + /* x^29696 mod p(x)` << 1, x^29760 mod p(x)` << 1 */ + { 0x00000001ab2f5afc, 0x00000000fa366d3a }, + /* x^28672 mod p(x)` << 1, x^28736 mod p(x)` << 1 */ + { 0x0000000074a4ebd4, 0x00000001a2bb34f0 }, + /* x^27648 mod p(x)` << 1, x^27712 mod p(x)` << 1 */ + { 0x00000001d7ab3a4c, 0x0000000028a9981e }, + /* x^26624 mod p(x)` << 1, x^26688 mod p(x)` << 1 */ + { 0x00000001a8da60c6, 0x00000001dbc672be }, + /* x^25600 mod p(x)` << 1, x^25664 mod p(x)` << 1 */ + { 0x000000013cf63820, 0x00000000b04d77f6 }, + /* x^24576 mod p(x)` << 1, x^24640 mod p(x)` << 1 */ + { 0x00000000bec12e1e, 0x0000000124400d96 }, + /* x^23552 mod p(x)` << 1, x^23616 mod p(x)` << 1 */ + { 0x00000001c6368010, 0x000000014ca4b414 }, + /* x^22528 mod p(x)` << 1, x^22592 mod p(x)` << 1 */ + { 0x00000001e6e78758, 0x000000012fe2c938 }, + /* x^21504 mod p(x)` << 1, x^21568 mod p(x)` << 1 */ + { 0x000000008d7f2b3c, 0x00000001faed01e6 }, + /* x^20480 mod p(x)` << 1, x^20544 mod p(x)` << 1 */ + { 0x000000016b4a156e, 0x000000007e80ecfe }, + /* x^19456 mod p(x)` << 1, x^19520 mod p(x)` << 1 */ + { 0x00000001c63cfeb6, 0x0000000098daee94 }, + /* x^18432 mod p(x)` << 1, x^18496 mod p(x)` << 1 */ + { 0x000000015f902670, 0x000000010a04edea }, + /* x^17408 mod p(x)` << 1, x^17472 mod p(x)` << 1 */ + { 0x00000001cd5de11e, 0x00000001c00b4524 }, + /* x^16384 mod p(x)` << 1, x^16448 mod p(x)` << 1 */ + { 0x000000001acaec54, 0x0000000170296550 }, + /* x^15360 mod p(x)` << 1, x^15424 mod p(x)` << 1 */ + { 0x000000002bd0ca78, 0x0000000181afaa48 }, + /* x^14336 mod p(x)` << 1, x^14400 mod p(x)` << 1 */ + { 0x0000000032d63d5c, 0x0000000185a31ffa }, + /* x^13312 mod p(x)` << 1, x^13376 mod p(x)` << 1 */ + { 0x000000001c6d4e4c, 0x000000002469f608 }, + /* x^12288 mod p(x)` << 1, x^12352 mod p(x)` << 1 */ + { 0x0000000106a60b92, 0x000000006980102a }, + /* x^11264 mod p(x)` << 1, x^11328 mod p(x)` << 1 */ + { 0x00000000d3855e12, 0x0000000111ea9ca8 }, + /* x^10240 mod p(x)` << 1, x^10304 mod p(x)` << 1 */ + { 0x00000000e3125636, 0x00000001bd1d29ce }, + /* x^9216 mod p(x)` << 1, x^9280 mod p(x)` << 1 */ + { 0x000000009e8f7ea4, 0x00000001b34b9580 }, + /* x^8192 mod p(x)` << 1, x^8256 mod p(x)` << 1 */ + { 0x00000001c82e562c, 0x000000003076054e }, + /* x^7168 mod p(x)` << 1, x^7232 mod p(x)` << 1 */ + { 0x00000000ca9f09ce, 0x000000012a608ea4 }, + /* x^6144 mod p(x)` << 1, x^6208 mod p(x)` << 1 */ + { 0x00000000c63764e6, 0x00000000784d05fe }, + /* x^5120 mod p(x)` << 1, x^5184 mod p(x)` << 1 */ + { 0x0000000168d2e49e, 0x000000016ef0d82a }, + /* x^4096 mod p(x)` << 1, x^4160 mod p(x)` << 1 */ + { 0x00000000e986c148, 0x0000000075bda454 }, + /* x^3072 mod p(x)` << 1, x^3136 mod p(x)` << 1 */ + { 0x00000000cfb65894, 0x000000003dc0a1c4 }, + /* x^2048 mod p(x)` << 1, x^2112 mod p(x)` << 1 */ + { 0x0000000111cadee4, 0x00000000e9a5d8be }, + /* x^1024 mod p(x)` << 1, x^1088 mod p(x)` << 1 */ + { 0x0000000171fb63ce, 0x00000001609bc4b4 } +#endif /* __LITTLE_ENDIAN__ */ + }; + +/* Reduce final 1024-2048 bits to 64 bits, shifting 32 bits to include the trailing 32 bits of zeros */ + +static const __vector unsigned long long vcrc_short_const[16] + __attribute__((aligned (16))) = { +#ifdef __LITTLE_ENDIAN__ + /* x^1952 mod p(x) , x^1984 mod p(x) , x^2016 mod p(x) , x^2048 mod p(x) */ + { 0x5cf015c388e56f72, 0x7fec2963e5bf8048 }, + /* x^1824 mod p(x) , x^1856 mod p(x) , x^1888 mod p(x) , x^1920 mod p(x) */ + { 0x963a18920246e2e6, 0x38e888d4844752a9 }, + /* x^1696 mod p(x) , x^1728 mod p(x) , x^1760 mod p(x) , x^1792 mod p(x) */ + { 0x419a441956993a31, 0x42316c00730206ad }, + /* x^1568 mod p(x) , x^1600 mod p(x) , x^1632 mod p(x) , x^1664 mod p(x) */ + { 0x924752ba2b830011, 0x543d5c543e65ddf9 }, + /* x^1440 mod p(x) , x^1472 mod p(x) , x^1504 mod p(x) , x^1536 mod p(x) */ + { 0x55bd7f9518e4a304, 0x78e87aaf56767c92 }, + /* x^1312 mod p(x) , x^1344 mod p(x) , x^1376 mod p(x) , x^1408 mod p(x) */ + { 0x6d76739fe0553f1e, 0x8f68fcec1903da7f }, + /* x^1184 mod p(x) , x^1216 mod p(x) , x^1248 mod p(x) , x^1280 mod p(x) */ + { 0xc133722b1fe0b5c3, 0x3f4840246791d588 }, + /* x^1056 mod p(x) , x^1088 mod p(x) , x^1120 mod p(x) , x^1152 mod p(x) */ + { 0x64b67ee0e55ef1f3, 0x34c96751b04de25a }, + /* x^928 mod p(x) , x^960 mod p(x) , x^992 mod p(x) , x^1024 mod p(x) */ + { 0x069db049b8fdb1e7, 0x156c8e180b4a395b }, + /* x^800 mod p(x) , x^832 mod p(x) , x^864 mod p(x) , x^896 mod p(x) */ + { 0xa11bfaf3c9e90b9e, 0xe0b99ccbe661f7be }, + /* x^672 mod p(x) , x^704 mod p(x) , x^736 mod p(x) , x^768 mod p(x) */ + { 0x817cdc5119b29a35, 0x041d37768cd75659 }, + /* x^544 mod p(x) , x^576 mod p(x) , x^608 mod p(x) , x^640 mod p(x) */ + { 0x1ce9d94b36c41f1c, 0x3a0777818cfaa965 }, + /* x^416 mod p(x) , x^448 mod p(x) , x^480 mod p(x) , x^512 mod p(x) */ + { 0x4f256efcb82be955, 0x0e148e8252377a55 }, + /* x^288 mod p(x) , x^320 mod p(x) , x^352 mod p(x) , x^384 mod p(x) */ + { 0xec1631edb2dea967, 0x9c25531d19e65dde }, + /* x^160 mod p(x) , x^192 mod p(x) , x^224 mod p(x) , x^256 mod p(x) */ + { 0x5d27e147510ac59a, 0x790606ff9957c0a6 }, + /* x^32 mod p(x) , x^64 mod p(x) , x^96 mod p(x) , x^128 mod p(x) */ + { 0xa66805eb18b8ea18, 0x82f63b786ea2d55c } +#else /* __LITTLE_ENDIAN__ */ + /* x^1952 mod p(x) , x^1984 mod p(x) , x^2016 mod p(x) , x^2048 mod p(x) */ + { 0x7fec2963e5bf8048, 0x5cf015c388e56f72 }, + /* x^1824 mod p(x) , x^1856 mod p(x) , x^1888 mod p(x) , x^1920 mod p(x) */ + { 0x38e888d4844752a9, 0x963a18920246e2e6 }, + /* x^1696 mod p(x) , x^1728 mod p(x) , x^1760 mod p(x) , x^1792 mod p(x) */ + { 0x42316c00730206ad, 0x419a441956993a31 }, + /* x^1568 mod p(x) , x^1600 mod p(x) , x^1632 mod p(x) , x^1664 mod p(x) */ + { 0x543d5c543e65ddf9, 0x924752ba2b830011 }, + /* x^1440 mod p(x) , x^1472 mod p(x) , x^1504 mod p(x) , x^1536 mod p(x) */ + { 0x78e87aaf56767c92, 0x55bd7f9518e4a304 }, + /* x^1312 mod p(x) , x^1344 mod p(x) , x^1376 mod p(x) , x^1408 mod p(x) */ + { 0x8f68fcec1903da7f, 0x6d76739fe0553f1e }, + /* x^1184 mod p(x) , x^1216 mod p(x) , x^1248 mod p(x) , x^1280 mod p(x) */ + { 0x3f4840246791d588, 0xc133722b1fe0b5c3 }, + /* x^1056 mod p(x) , x^1088 mod p(x) , x^1120 mod p(x) , x^1152 mod p(x) */ + { 0x34c96751b04de25a, 0x64b67ee0e55ef1f3 }, + /* x^928 mod p(x) , x^960 mod p(x) , x^992 mod p(x) , x^1024 mod p(x) */ + { 0x156c8e180b4a395b, 0x069db049b8fdb1e7 }, + /* x^800 mod p(x) , x^832 mod p(x) , x^864 mod p(x) , x^896 mod p(x) */ + { 0xe0b99ccbe661f7be, 0xa11bfaf3c9e90b9e }, + /* x^672 mod p(x) , x^704 mod p(x) , x^736 mod p(x) , x^768 mod p(x) */ + { 0x041d37768cd75659, 0x817cdc5119b29a35 }, + /* x^544 mod p(x) , x^576 mod p(x) , x^608 mod p(x) , x^640 mod p(x) */ + { 0x3a0777818cfaa965, 0x1ce9d94b36c41f1c }, + /* x^416 mod p(x) , x^448 mod p(x) , x^480 mod p(x) , x^512 mod p(x) */ + { 0x0e148e8252377a55, 0x4f256efcb82be955 }, + /* x^288 mod p(x) , x^320 mod p(x) , x^352 mod p(x) , x^384 mod p(x) */ + { 0x9c25531d19e65dde, 0xec1631edb2dea967 }, + /* x^160 mod p(x) , x^192 mod p(x) , x^224 mod p(x) , x^256 mod p(x) */ + { 0x790606ff9957c0a6, 0x5d27e147510ac59a }, + /* x^32 mod p(x) , x^64 mod p(x) , x^96 mod p(x) , x^128 mod p(x) */ + { 0x82f63b786ea2d55c, 0xa66805eb18b8ea18 } +#endif /* __LITTLE_ENDIAN__ */ + }; + +/* Barrett constants */ +/* 33 bit reflected Barrett constant m - (4^32)/n */ + +static const __vector unsigned long long v_Barrett_const[2] + __attribute__((aligned (16))) = { + /* x^64 div p(x) */ +#ifdef __LITTLE_ENDIAN__ + { 0x00000000dea713f1, 0x0000000000000000 }, + { 0x0000000105ec76f1, 0x0000000000000000 } +#else /* __LITTLE_ENDIAN__ */ + { 0x0000000000000000, 0x00000000dea713f1 }, + { 0x0000000000000000, 0x0000000105ec76f1 } +#endif /* __LITTLE_ENDIAN__ */ + }; +#endif /* POWER8_INTRINSICS */ + +#endif /* __ASSEMBLER__ */ diff --git a/contrib/crc32-vpmsum-cmake/vec_crc32.h b/contrib/crc32-vpmsum-cmake/vec_crc32.h new file mode 100644 index 00000000000..0ef13616b34 --- /dev/null +++ b/contrib/crc32-vpmsum-cmake/vec_crc32.h @@ -0,0 +1,29 @@ +#ifndef VEC_CRC32 +#define VEC_CRC32 + + +#ifdef __cplusplus +extern "C" { +#endif + +unsigned int crc32_vpmsum(unsigned int crc, const unsigned char *p, unsigned long len); + +static inline uint32_t crc32_ppc(uint64_t crc, unsigned char const *buffer, size_t len) +{ + unsigned char *emptybuffer; + if (!buffer) { + emptybuffer = (unsigned char *)malloc(len); + bzero(emptybuffer, len); + crc = crc32_vpmsum(crc, emptybuffer, len); + free(emptybuffer); + } else { + crc = crc32_vpmsum(crc, buffer, (unsigned long)len); + } + return crc; +} + +#ifdef __cplusplus +} +#endif + +#endif diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt index d8a7dba72ac..1bc1151b90b 100644 --- a/src/CMakeLists.txt +++ b/src/CMakeLists.txt @@ -364,6 +364,10 @@ if (TARGET ch_contrib::crc32_s390x) target_link_libraries(clickhouse_common_io PUBLIC ch_contrib::crc32_s390x) endif() +if (TARGET ch_contrib::crc32-vpmsum) + target_link_libraries(clickhouse_common_io PUBLIC ch_contrib::crc32-vpmsum) + endif() + dbms_target_link_libraries(PUBLIC ch_contrib::abseil_swiss_tables) target_link_libraries (clickhouse_common_io PUBLIC ch_contrib::abseil_swiss_tables) diff --git a/src/Common/HashTable/Hash.h b/src/Common/HashTable/Hash.h index 01758c1b9fb..c7342d061d8 100644 --- a/src/Common/HashTable/Hash.h +++ b/src/Common/HashTable/Hash.h @@ -48,6 +48,10 @@ inline DB::UInt64 intHash64(DB::UInt64 x) #include #endif +#if (defined(__PPC64__) || defined(__powerpc64__)) && __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ +#include "vec_crc32.h" +#endif + #if defined(__s390x__) && __BYTE_ORDER__==__ORDER_BIG_ENDIAN__ #include @@ -89,6 +93,8 @@ inline DB::UInt64 intHashCRC32(DB::UInt64 x) return __crc32cd(-1U, x); #elif defined(__s390x__) && __BYTE_ORDER__ == __ORDER_BIG_ENDIAN__ return s390x_crc32(-1U, x) +#elif (defined(__PPC64__) || defined(__powerpc64__)) && __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ + return crc32_ppc(-1U, reinterpret_cast(&x), sizeof(x)); #else /// On other platforms we do not have CRC32. NOTE This can be confusing. /// NOTE: consider using intHash32() @@ -103,6 +109,8 @@ inline DB::UInt64 intHashCRC32(DB::UInt64 x, DB::UInt64 updated_value) return __crc32cd(static_cast(updated_value), x); #elif defined(__s390x__) && __BYTE_ORDER__==__ORDER_BIG_ENDIAN__ return s390x_crc32(updated_value, x); +#elif (defined(__PPC64__) || defined(__powerpc64__)) && __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ + return crc32_ppc(updated_value, reinterpret_cast(&x), sizeof(x)); #else /// On other platforms we do not have CRC32. NOTE This can be confusing. return intHash64(x) ^ updated_value; diff --git a/src/Functions/CMakeLists.txt b/src/Functions/CMakeLists.txt index e9810e918b4..45543f57b37 100644 --- a/src/Functions/CMakeLists.txt +++ b/src/Functions/CMakeLists.txt @@ -86,6 +86,10 @@ if (TARGET ch_contrib::rapidjson) list (APPEND PRIVATE_LIBS ch_contrib::rapidjson) endif() +if (TARGET ch_contrib::crc32-vpmsum) + list (APPEND PUBLIC_LIBS ch_contrib::crc32-vpmsum) +endif() + add_subdirectory(GatherUtils) list (APPEND PRIVATE_LIBS clickhouse_functions_gatherutils) diff --git a/src/Functions/FunctionsStringHash.cpp b/src/Functions/FunctionsStringHash.cpp index 174acebe979..bf0b7463a5d 100644 --- a/src/Functions/FunctionsStringHash.cpp +++ b/src/Functions/FunctionsStringHash.cpp @@ -14,6 +14,10 @@ #include +#if (defined(__PPC64__) || defined(__powerpc64__)) && __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ +#include "vec_crc32.h" +#endif + namespace DB { @@ -38,6 +42,8 @@ struct Hash return __crc32cd(static_cast(crc), val); #elif defined(__s390x__) && __BYTE_ORDER__==__ORDER_BIG_ENDIAN__ return s390x_crc32(crc, val); +#elif (defined(__PPC64__) || defined(__powerpc64__)) && __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ + return crc32_ppc(crc, reinterpret_cast(&val), sizeof(val)); #else throw Exception("String hash is not implemented without sse4.2 support", ErrorCodes::NOT_IMPLEMENTED); #endif @@ -51,6 +57,8 @@ struct Hash return __crc32cw(crc, val); #elif defined(__s390x__) && __BYTE_ORDER__==__ORDER_BIG_ENDIAN__ return s390x_crc32_u32(crc, val); +#elif (defined(__PPC64__) || defined(__powerpc64__)) && __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ + return crc32_ppc(crc, reinterpret_cast(&val), sizeof(val)); #else throw Exception("String hash is not implemented without sse4.2 support", ErrorCodes::NOT_IMPLEMENTED); #endif @@ -64,6 +72,8 @@ struct Hash return __crc32ch(crc, val); #elif defined(__s390x__) && __BYTE_ORDER__==__ORDER_BIG_ENDIAN__ return s390x_crc32_u16(crc, val); +#elif (defined(__PPC64__) || defined(__powerpc64__)) && __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ + return crc32_ppc(crc, reinterpret_cast(&val), sizeof(val)); #else throw Exception("String hash is not implemented without sse4.2 support", ErrorCodes::NOT_IMPLEMENTED); #endif @@ -77,6 +87,8 @@ struct Hash return __crc32cb(crc, val); #elif defined(__s390x__) && __BYTE_ORDER__==__ORDER_BIG_ENDIAN__ return s390x_crc32_u8(crc, val); +#elif (defined(__PPC64__) || defined(__powerpc64__)) && __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ + return crc32_ppc(crc, reinterpret_cast(&val), sizeof(val)); #else throw Exception("String hash is not implemented without sse4.2 support", ErrorCodes::NOT_IMPLEMENTED); #endif diff --git a/src/Functions/FunctionsStringSimilarity.cpp b/src/Functions/FunctionsStringSimilarity.cpp index 802aafc2042..87aa0f4b3f7 100644 --- a/src/Functions/FunctionsStringSimilarity.cpp +++ b/src/Functions/FunctionsStringSimilarity.cpp @@ -24,6 +24,10 @@ # include #endif +#if (defined(__PPC64__) || defined(__powerpc64__)) && __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ +#include "vec_crc32.h" +#endif + namespace DB { /** Distance function implementation. @@ -72,6 +76,8 @@ struct NgramDistanceImpl return __crc32cd(code_points[2], combined) & 0xFFFFu; #elif defined(__s390x__) && __BYTE_ORDER__ == __ORDER_BIG_ENDIAN__ return s390x_crc32(code_points[2], combined) & 0xFFFFu; +#elif (defined(__PPC64__) || defined(__powerpc64__)) && __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ + return crc32_ppc(code_points[2], reinterpret_cast(&combined), sizeof(combined)) & 0xFFFFu; #else return (intHashCRC32(combined) ^ intHashCRC32(code_points[2])) & 0xFFFFu; #endif diff --git a/tests/queries/0_stateless/01016_simhash_minhash.ppc64le.reference b/tests/queries/0_stateless/01016_simhash_minhash.ppc64le.reference new file mode 100644 index 00000000000..2acad33320b --- /dev/null +++ b/tests/queries/0_stateless/01016_simhash_minhash.ppc64le.reference @@ -0,0 +1,148 @@ +18446744073709551615 +1737075136 +1737075136 +4018781633 +4018781633 +1846985414 +1846985414 +1846985414 +1846985414 +(10693559443859979498,10693559443859979498) +(12279482788274235946,6436413987527322272) +(12279482788274235946,6436413987527322272) +(13257488272755813409,6436413987527322272) +(13257488272755813409,6436413987527322272) +(13762864994695140861,13762864994695140861) +(13762864994695140861,13762864994695140861) +(13762864994695140861,13762864994695140861) +(13762864994695140861,13762864994695140861) +3023525975 +3040303199 +3023509591 +3023510623 +3040303191 +3040303191 +3023510615 +3023510615 +1999952988 +926211140 +1999699532 +1999683148 +1999952988 +926211140 +1999699532 +1999683148 +(16071125717475221203,9592059329600248798) +(16071125717475221203,1914899959549098907) +(16071125717475221203,7986182634218042944) +(16071125717475221203,7986182634218042944) +(16071125717475221203,9592059329600248798) +(16071125717475221203,1914899959549098907) +(16071125717475221203,7986182634218042944) +(16071125717475221203,7986182634218042944) +(10576877560263640956,4278250516018530743) +(16211512098526494023,11479872370566432466) +(13515070557027359649,17725505493832406849) +(12589381623326290380,575343713614534202) +(10576877560263640956,4278250516018530743) +(16211512098526494023,11479872370566432466) +(13515070557027359649,17725505493832406849) +(12589381623326290380,575343713614534202) +uniqExact 6 +ngramSimHash +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all your structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.\n:::::::\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 2 1211135069 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all of your structured data into the system, and it is immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 1546679389 +ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency.\nClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. Downtime of a single node or the whole datacenter wont affect the systems availability for both reads and writes.\nClickHouse is simple and works out-of-the-box. It streamlines all your data processing: ingest all your structured data into the system and it becomes instantly available for building reports. SQL dialect allows expressing the desired result without involving any custom non-standard API that could be found in some alternative systems. 1 2293265501 +ClickHouse makes full use of all available hardware to process every request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (only used columns after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid single points of failure. Downtime for one site or the entire data center will not affect the system\'s read and write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they immediately become available for building reports. The SQL dialect allows you to express the desired result without resorting to any non-standard APIs that can be found in some alternative systems. 1 3392173149 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (used columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the system\'s read / write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they are immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 3627054169 +ngramSimHashCaseInsensitive +ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency.\nClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. Downtime of a single node or the whole datacenter wont affect the systems availability for both reads and writes.\nClickHouse is simple and works out-of-the-box. It streamlines all your data processing: ingest all your structured data into the system and it becomes instantly available for building reports. SQL dialect allows expressing the desired result without involving any custom non-standard API that could be found in some alternative systems. 1 2291168349 +ClickHouse makes full use of all available hardware to process every request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (only used columns after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid single points of failure. Downtime for one site or the entire data center will not affect the system\'s read and write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they immediately become available for building reports. The SQL dialect allows you to express the desired result without resorting to any non-standard APIs that can be found in some alternative systems.\n:::::::\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all your structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.\n:::::::\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 3 3358618717 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all of your structured data into the system, and it is immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 3425727581 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (used columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the system\'s read / write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they are immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 3627054429 +ngramSimHashUTF8 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all your structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.\n:::::::\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 2 1211135069 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all of your structured data into the system, and it is immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 1546679389 +ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency.\nClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. Downtime of a single node or the whole datacenter wont affect the systems availability for both reads and writes.\nClickHouse is simple and works out-of-the-box. It streamlines all your data processing: ingest all your structured data into the system and it becomes instantly available for building reports. SQL dialect allows expressing the desired result without involving any custom non-standard API that could be found in some alternative systems. 1 2284876893 +ClickHouse makes full use of all available hardware to process every request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (only used columns after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid single points of failure. Downtime for one site or the entire data center will not affect the system\'s read and write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they immediately become available for building reports. The SQL dialect allows you to express the desired result without resorting to any non-standard APIs that can be found in some alternative systems. 1 3459282013 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (used columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the system\'s read / write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they are immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 3694163037 +ngramSimHashCaseInsensitiveUTF8 +ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency.\nClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. Downtime of a single node or the whole datacenter wont affect the systems availability for both reads and writes.\nClickHouse is simple and works out-of-the-box. It streamlines all your data processing: ingest all your structured data into the system and it becomes instantly available for building reports. SQL dialect allows expressing the desired result without involving any custom non-standard API that could be found in some alternative systems. 1 2291168349 +ClickHouse makes full use of all available hardware to process every request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (only used columns after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid single points of failure. Downtime for one site or the entire data center will not affect the system\'s read and write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they immediately become available for building reports. The SQL dialect allows you to express the desired result without resorting to any non-standard APIs that can be found in some alternative systems.\n:::::::\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all your structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.\n:::::::\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 3 3358618717 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all of your structured data into the system, and it is immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 3425727581 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (used columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the system\'s read / write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they are immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 3627054429 +wordShingleSimHash +ClickHouse makes full use of all available hardware to process every request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (only used columns after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid single points of failure. Downtime for one site or the entire data center will not affect the system\'s read and write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they immediately become available for building reports. The SQL dialect allows you to express the desired result without resorting to any non-standard APIs that can be found in some alternative systems. 1 10637533 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (used columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the system\'s read / write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they are immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 171136201 +ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency.\nClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. Downtime of a single node or the whole datacenter wont affect the systems availability for both reads and writes.\nClickHouse is simple and works out-of-the-box. It streamlines all your data processing: ingest all your structured data into the system and it becomes instantly available for building reports. SQL dialect allows expressing the desired result without involving any custom non-standard API that could be found in some alternative systems. 1 209864029 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all your structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 413353165 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 413353677 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all of your structured data into the system, and it is immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 418595033 +wordShingleSimHashCaseInsensitive +ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency.\nClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. Downtime of a single node or the whole datacenter wont affect the systems availability for both reads and writes.\nClickHouse is simple and works out-of-the-box. It streamlines all your data processing: ingest all your structured data into the system and it becomes instantly available for building reports. SQL dialect allows expressing the desired result without involving any custom non-standard API that could be found in some alternative systems. 1 218252892 +ClickHouse makes full use of all available hardware to process every request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (only used columns after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid single points of failure. Downtime for one site or the entire data center will not affect the system\'s read and write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they immediately become available for building reports. The SQL dialect allows you to express the desired result without resorting to any non-standard APIs that can be found in some alternative systems. 1 1218592985 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (used columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the system\'s read / write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they are immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 1613919433 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all your structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 2080524225 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 2088912577 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all of your structured data into the system, and it is immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 2094163657 +wordShingleSimHashUTF8 +ClickHouse makes full use of all available hardware to process every request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (only used columns after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid single points of failure. Downtime for one site or the entire data center will not affect the system\'s read and write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they immediately become available for building reports. The SQL dialect allows you to express the desired result without resorting to any non-standard APIs that can be found in some alternative systems. 1 10637533 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (used columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the system\'s read / write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they are immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 171136201 +ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency.\nClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. Downtime of a single node or the whole datacenter wont affect the systems availability for both reads and writes.\nClickHouse is simple and works out-of-the-box. It streamlines all your data processing: ingest all your structured data into the system and it becomes instantly available for building reports. SQL dialect allows expressing the desired result without involving any custom non-standard API that could be found in some alternative systems. 1 209864029 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all your structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 413353165 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 413353677 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all of your structured data into the system, and it is immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 418595033 +wordShingleSimHashCaseInsensitiveUTF8 +ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency.\nClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. Downtime of a single node or the whole datacenter wont affect the systems availability for both reads and writes.\nClickHouse is simple and works out-of-the-box. It streamlines all your data processing: ingest all your structured data into the system and it becomes instantly available for building reports. SQL dialect allows expressing the desired result without involving any custom non-standard API that could be found in some alternative systems. 1 218252892 +ClickHouse makes full use of all available hardware to process every request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (only used columns after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid single points of failure. Downtime for one site or the entire data center will not affect the system\'s read and write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they immediately become available for building reports. The SQL dialect allows you to express the desired result without resorting to any non-standard APIs that can be found in some alternative systems. 1 1218592985 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (used columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the system\'s read / write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they are immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 1613919433 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all your structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 2080524225 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 2088912577 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all of your structured data into the system, and it is immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 2094163657 +ngramMinHash +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (used columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the system\'s read / write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they are immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 (2793448378579182412,5526633106516004292) +ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency.\nClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. Downtime of a single node or the whole datacenter wont affect the systems availability for both reads and writes.\nClickHouse is simple and works out-of-the-box. It streamlines all your data processing: ingest all your structured data into the system and it becomes instantly available for building reports. SQL dialect allows expressing the desired result without involving any custom non-standard API that could be found in some alternative systems. 1 (8530889421347045182,5150364204263408031) +ClickHouse makes full use of all available hardware to process every request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (only used columns after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid single points of failure. Downtime for one site or the entire data center will not affect the system\'s read and write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they immediately become available for building reports. The SQL dialect allows you to express the desired result without resorting to any non-standard APIs that can be found in some alternative systems. 1 (8992738078100405992,5526633106516004292) +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all of your structured data into the system, and it is immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.\n:::::::\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all your structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.\n:::::::\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 3 (15193387305258759701,5526633106516004292) +ngramMinHashCaseInsensitive +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (used columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the system\'s read / write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they are immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 (2793448378579182412,5526633106516004292) +ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency.\nClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. Downtime of a single node or the whole datacenter wont affect the systems availability for both reads and writes.\nClickHouse is simple and works out-of-the-box. It streamlines all your data processing: ingest all your structured data into the system and it becomes instantly available for building reports. SQL dialect allows expressing the desired result without involving any custom non-standard API that could be found in some alternative systems. 1 (8530889421347045182,5150364204263408031) +ClickHouse makes full use of all available hardware to process every request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (only used columns after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid single points of failure. Downtime for one site or the entire data center will not affect the system\'s read and write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they immediately become available for building reports. The SQL dialect allows you to express the desired result without resorting to any non-standard APIs that can be found in some alternative systems. 1 (8992738078100405992,5526633106516004292) +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all of your structured data into the system, and it is immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.\n:::::::\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all your structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.\n:::::::\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 3 (15193387305258759701,5526633106516004292) +ngramMinHashUTF8 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (used columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the system\'s read / write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they are immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 (2793448378579182412,5526633106516004292) +ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency.\nClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. Downtime of a single node or the whole datacenter wont affect the systems availability for both reads and writes.\nClickHouse is simple and works out-of-the-box. It streamlines all your data processing: ingest all your structured data into the system and it becomes instantly available for building reports. SQL dialect allows expressing the desired result without involving any custom non-standard API that could be found in some alternative systems. 1 (8530889421347045182,5150364204263408031) +ClickHouse makes full use of all available hardware to process every request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (only used columns after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid single points of failure. Downtime for one site or the entire data center will not affect the system\'s read and write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they immediately become available for building reports. The SQL dialect allows you to express the desired result without resorting to any non-standard APIs that can be found in some alternative systems. 1 (8992738078100405992,5526633106516004292) +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all of your structured data into the system, and it is immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.\n:::::::\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all your structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.\n:::::::\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 3 (15193387305258759701,5526633106516004292) +ngramMinHashCaseInsensitiveUTF8 +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (used columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the system\'s read / write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they are immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 (2793448378579182412,5526633106516004292) +ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency.\nClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. Downtime of a single node or the whole datacenter wont affect the systems availability for both reads and writes.\nClickHouse is simple and works out-of-the-box. It streamlines all your data processing: ingest all your structured data into the system and it becomes instantly available for building reports. SQL dialect allows expressing the desired result without involving any custom non-standard API that could be found in some alternative systems. 1 (8530889421347045182,5150364204263408031) +ClickHouse makes full use of all available hardware to process every request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (only used columns after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid single points of failure. Downtime for one site or the entire data center will not affect the system\'s read and write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they immediately become available for building reports. The SQL dialect allows you to express the desired result without resorting to any non-standard APIs that can be found in some alternative systems. 1 (8992738078100405992,5526633106516004292) +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all of your structured data into the system, and it is immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.\n:::::::\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all your structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.\n:::::::\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 3 (15193387305258759701,5526633106516004292) +wordShingleMinHash +ClickHouse makes full use of all available hardware to process every request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (only used columns after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid single points of failure. Downtime for one site or the entire data center will not affect the system\'s read and write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they immediately become available for building reports. The SQL dialect allows you to express the desired result without resorting to any non-standard APIs that can be found in some alternative systems. 1 (3409292695558556998,3242671779450421938) +ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency.\nClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. Downtime of a single node or the whole datacenter wont affect the systems availability for both reads and writes.\nClickHouse is simple and works out-of-the-box. It streamlines all your data processing: ingest all your structured data into the system and it becomes instantly available for building reports. SQL dialect allows expressing the desired result without involving any custom non-standard API that could be found in some alternative systems. 1 (11981468198903037199,5500630346333489583) +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (used columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the system\'s read / write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they are immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.\n:::::::\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all of your structured data into the system, and it is immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 2 (12852656749419794093,678630951345180105) +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 (13105381013738345838,410122209669519134) +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all your structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 (13105381013738345838,3365040177160857031) +wordShingleMinHashCaseInsensitive +ClickHouse makes full use of all available hardware to process every request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (only used columns after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid single points of failure. Downtime for one site or the entire data center will not affect the system\'s read and write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they immediately become available for building reports. The SQL dialect allows you to express the desired result without resorting to any non-standard APIs that can be found in some alternative systems. 1 (712181695272576370,125062659592971094) +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (used columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the system\'s read / write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they are immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.\n:::::::\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all of your structured data into the system, and it is immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 2 (3404326999173181417,12067981913120463876) +ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency.\nClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. Downtime of a single node or the whole datacenter wont affect the systems availability for both reads and writes.\nClickHouse is simple and works out-of-the-box. It streamlines all your data processing: ingest all your structured data into the system and it becomes instantly available for building reports. SQL dialect allows expressing the desired result without involving any custom non-standard API that could be found in some alternative systems. 1 (13918035273694643957,5500630346333489583) +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all your structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 (14132553626943388792,12467125901844798869) +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 (14132553626943388792,17567683680214055861) +wordShingleMinHashUTF8 +ClickHouse makes full use of all available hardware to process every request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (only used columns after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid single points of failure. Downtime for one site or the entire data center will not affect the system\'s read and write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they immediately become available for building reports. The SQL dialect allows you to express the desired result without resorting to any non-standard APIs that can be found in some alternative systems. 1 (3409292695558556998,3242671779450421938) +ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency.\nClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. Downtime of a single node or the whole datacenter wont affect the systems availability for both reads and writes.\nClickHouse is simple and works out-of-the-box. It streamlines all your data processing: ingest all your structured data into the system and it becomes instantly available for building reports. SQL dialect allows expressing the desired result without involving any custom non-standard API that could be found in some alternative systems. 1 (11981468198903037199,5500630346333489583) +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (used columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the system\'s read / write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they are immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.\n:::::::\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all of your structured data into the system, and it is immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 2 (12852656749419794093,678630951345180105) +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 (13105381013738345838,410122209669519134) +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all your structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 (13105381013738345838,3365040177160857031) +wordShingleMinHashCaseInsensitiveUTF8 +ClickHouse makes full use of all available hardware to process every request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (only used columns after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid single points of failure. Downtime for one site or the entire data center will not affect the system\'s read and write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they immediately become available for building reports. The SQL dialect allows you to express the desired result without resorting to any non-standard APIs that can be found in some alternative systems. 1 (712181695272576370,125062659592971094) +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (used columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the system\'s read / write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they are immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.\n:::::::\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all of your structured data into the system, and it is immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 2 (3404326999173181417,12067981913120463876) +ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency.\nClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. Downtime of a single node or the whole datacenter wont affect the systems availability for both reads and writes.\nClickHouse is simple and works out-of-the-box. It streamlines all your data processing: ingest all your structured data into the system and it becomes instantly available for building reports. SQL dialect allows expressing the desired result without involving any custom non-standard API that could be found in some alternative systems. 1 (13918035273694643957,5500630346333489583) +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all your structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 (14132553626943388792,12467125901844798869) +ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. 1 (14132553626943388792,17567683680214055861) +code 69: Second argument (shingle size) of function wordShingleSimHash cannot be greater then 25: While processing wordShingleSimHash('foobar', 9223372036854775807)None +code 69: Second argument (shingle size) of function wordShingleSimHash cannot be greater then 25: While processing wordShingleSimHash('foobar', 1001)None +code 69: Second argument (shingle size) of function wordShingleSimHash cannot be zero: While processing wordShingleSimHash('foobar', 0)None diff --git a/tests/queries/0_stateless/01016_simhash_minhash.python b/tests/queries/0_stateless/01016_simhash_minhash.python new file mode 100644 index 00000000000..1d6eae456c1 --- /dev/null +++ b/tests/queries/0_stateless/01016_simhash_minhash.python @@ -0,0 +1,394 @@ +#!/usr/bin/env python3 +import os +import socket +import sys +from scipy import stats +import pandas as pd +import numpy as np +import shutil +import platform + +import uuid + +CLICKHOUSE_HOST = os.environ.get('CLICKHOUSE_HOST', '127.0.0.1') +CLICKHOUSE_PORT = int(os.environ.get('CLICKHOUSE_PORT_TCP', '900000')) +CLICKHOUSE_DATABASE = os.environ.get('CLICKHOUSE_DATABASE', 'default') + + +CURDIR = os.path.dirname(os.path.realpath(__file__)) +sys.path.insert(0, os.path.join(CURDIR, 'helpers')) + +from pure_http_client import ClickHouseClient + +if platform.machine() == "ppc64le": + shutil.copyfile(CURDIR + "/01016_simhash_minhash.ppc64le.reference", CURDIR + "/01016_simhash_minhash.reference") +elif platform.machine() == "x86_64" : + shutil.copyfile(CURDIR + "/01016_simhash_minhash.x86_64.reference", CURDIR + "/01016_simhash_minhash.reference") + +def writeVarUInt(x, ba): + for _ in range(0, 9): + + byte = x & 0x7F + if x > 0x7F: + byte |= 0x80 + + ba.append(byte) + + x >>= 7 + if x == 0: + return + +def writeStringBinary(s, ba): + b = bytes(s, 'utf-8') + writeVarUInt(len(s), ba) + ba.extend(b) + +def readStrict(s, size = 1): + res = bytearray() + while size: + cur = s.recv(size) + # if not res: + # raise "Socket is closed" + size -= len(cur) + res.extend(cur) + + return res + +def readUInt(s, size=1): + res = readStrict(s, size) + val = 0 + for i in range(len(res)): + val += res[i] << (i * 8) + return val + +def readUInt8(s): + return readUInt(s) + +def readUInt16(s): + return readUInt(s, 2) + +def readUInt32(s): + return readUInt(s, 4) + +def readUInt64(s): + return readUInt(s, 8) + +def readVarUInt(s): + x = 0 + for i in range(9): + byte = readStrict(s)[0] + x |= (byte & 0x7F) << (7 * i) + + if not byte & 0x80: + return x + + return x + +def readStringBinary(s): + size = readVarUInt(s) + s = readStrict(s, size) + return s.decode('utf-8') + +def sendHello(s): + ba = bytearray() + writeVarUInt(0, ba) # Hello + writeStringBinary('simple native protocol', ba) + writeVarUInt(21, ba) + writeVarUInt(9, ba) + writeVarUInt(54449, ba) + writeStringBinary('default', ba) # database + writeStringBinary('default', ba) # user + writeStringBinary('', ba) # pwd + s.sendall(ba) + + +def receiveHello(s): + p_type = readVarUInt(s) + assert (p_type == 0) # Hello + server_name = readStringBinary(s) + # print("Server name: ", server_name) + server_version_major = readVarUInt(s) + # print("Major: ", server_version_major) + server_version_minor = readVarUInt(s) + # print("Minor: ", server_version_minor) + server_revision = readVarUInt(s) + # print("Revision: ", server_revision) + server_timezone = readStringBinary(s) + # print("Timezone: ", server_timezone) + server_display_name = readStringBinary(s) + # print("Display name: ", server_display_name) + server_version_patch = readVarUInt(s) + # print("Version patch: ", server_version_patch) + +def serializeClientInfo(ba, query_id): + writeStringBinary('default', ba) # initial_user + writeStringBinary(query_id, ba) # initial_query_id + writeStringBinary('127.0.0.1:9000', ba) # initial_address + ba.extend([0] * 8) # initial_query_start_time_microseconds + ba.append(1) # TCP + writeStringBinary('os_user', ba) # os_user + writeStringBinary('client_hostname', ba) # client_hostname + writeStringBinary('client_name', ba) # client_name + writeVarUInt(21, ba) + writeVarUInt(9, ba) + writeVarUInt(54449, ba) + writeStringBinary('', ba) # quota_key + writeVarUInt(0, ba) # distributed_depth + writeVarUInt(1, ba) # client_version_patch + ba.append(0) # No telemetry + +def sendQuery(s, query): + ba = bytearray() + query_id = uuid.uuid4().hex + writeVarUInt(1, ba) # query + writeStringBinary(query_id, ba) + + ba.append(1) # INITIAL_QUERY + + # client info + serializeClientInfo(ba, query_id) + + writeStringBinary('', ba) # No settings + writeStringBinary('', ba) # No interserver secret + writeVarUInt(2, ba) # Stage - Complete + ba.append(0) # No compression + writeStringBinary(query, ba) # query, finally + s.sendall(ba) + +def serializeBlockInfo(ba): + writeVarUInt(1, ba) # 1 + ba.append(0) # is_overflows + writeVarUInt(2, ba) # 2 + writeVarUInt(0, ba) # 0 + ba.extend([0] * 4) # bucket_num + +def sendEmptyBlock(s): + ba = bytearray() + writeVarUInt(2, ba) # Data + writeStringBinary('', ba) + serializeBlockInfo(ba) + writeVarUInt(0, ba) # rows + writeVarUInt(0, ba) # columns + s.sendall(ba) + +def assertPacket(packet, expected): + assert(packet == expected), packet + +def readException(s): + code = readUInt32(s) + name = readStringBinary(s) + text = readStringBinary(s) + readStringBinary(s) # trace + assertPacket(readUInt8(s), 0) # has_nested + sys.stdout.write("code {}: {}".format(code, text.replace('DB::Exception:', ''))) + + +def test(): + client = ClickHouseClient() + + res = client.query("SELECT ngramSimHash('')") + sys.stdout.write(res) + res=client.query("SELECT ngramSimHash('what a cute cat.')") + sys.stdout.write(res) + res = client.query("SELECT ngramSimHashCaseInsensitive('what a cute cat.')") + sys.stdout.write(res) + res = client.query("SELECT ngramSimHashUTF8('what a cute cat.')") + sys.stdout.write(res) + res = client.query("SELECT ngramSimHashCaseInsensitiveUTF8('what a cute cat.')") + sys.stdout.write(res) + res = client.query("SELECT wordShingleSimHash('what a cute cat.')") + sys.stdout.write(res) + res = client.query("SELECT wordShingleSimHashCaseInsensitive('what a cute cat.')") + sys.stdout.write(res) + res = client.query("SELECT wordShingleSimHashUTF8('what a cute cat.')") + sys.stdout.write(res) + res = client.query("SELECT wordShingleSimHashCaseInsensitiveUTF8('what a cute cat.')") + sys.stdout.write(res) + + res = client.query("SELECT ngramMinHash('')") + sys.stdout.write(res) + res = client.query("SELECT ngramMinHash('what a cute cat.')") + sys.stdout.write(res) + res = client.query("SELECT ngramMinHashCaseInsensitive('what a cute cat.')") + sys.stdout.write(res) + res = client.query("SELECT ngramMinHashUTF8('what a cute cat.')") + sys.stdout.write(res) + res = client.query("SELECT ngramMinHashCaseInsensitiveUTF8('what a cute cat.')") + sys.stdout.write(res) + res = client.query("SELECT wordShingleMinHash('what a cute cat.')") + sys.stdout.write(res) + res = client.query("SELECT wordShingleMinHashCaseInsensitive('what a cute cat.')") + sys.stdout.write(res) + res = client.query("SELECT wordShingleMinHashUTF8('what a cute cat.')") + sys.stdout.write(res) + res = client.query("SELECT wordShingleMinHashCaseInsensitiveUTF8('what a cute cat.')") + sys.stdout.write(res) + + client.query("DROP TABLE IF EXISTS defaults") + client.query("CREATE TABLE defaults(s String) ENGINE = Memory()") + client.query("INSERT INTO defaults values ('It is the latest occurrence of the Southeast European haze, the issue that occurs in constant intensity during every wet season. It has mainly been caused by forest fires resulting from illegal slash-and-burn clearing performed on behalf of the palm oil industry in Kazakhstan, principally on the islands, which then spread quickly in the dry season.') ('It is the latest occurrence of the Southeast Asian haze, the issue that occurs in constant intensity during every wet season. It has mainly been caused by forest fires resulting from illegal slash-and-burn clearing performed on behalf of the palm oil industry in Kazakhstan, principally on the islands, which then spread quickly in the dry season.')") + + res = client.query("SELECT ngramSimHash(s) FROM defaults") + sys.stdout.write(res) + res = client.query("SELECT ngramSimHashCaseInsensitive(s) FROM defaults") + sys.stdout.write(res) + res = client.query("SELECT ngramSimHashUTF8(s) FROM defaults") + sys.stdout.write(res) + res = client.query("SELECT ngramSimHashCaseInsensitiveUTF8(s) FROM defaults") + sys.stdout.write(res) + res = client.query("SELECT wordShingleSimHash(s) FROM defaults") + sys.stdout.write(res) + res = client.query("SELECT wordShingleSimHashCaseInsensitive(s) FROM defaults") + sys.stdout.write(res) + res = client.query("SELECT wordShingleSimHashUTF8(s) FROM defaults") + sys.stdout.write(res) + res = client.query("SELECT wordShingleSimHashCaseInsensitiveUTF8(s) FROM defaults") + sys.stdout.write(res) + + res = client.query("SELECT ngramMinHash(s) FROM defaults") + sys.stdout.write(res) + res = client.query("SELECT ngramMinHashCaseInsensitive(s) FROM defaults") + sys.stdout.write(res) + res = client.query("SELECT ngramMinHashUTF8(s) FROM defaults") + sys.stdout.write(res) + res = client.query("SELECT ngramMinHashCaseInsensitiveUTF8(s) FROM defaults") + sys.stdout.write(res) + res = client.query("SELECT wordShingleMinHash(s) FROM defaults") + sys.stdout.write(res) + res = client.query("SELECT wordShingleMinHashCaseInsensitive(s) FROM defaults") + sys.stdout.write(res) + res = client.query("SELECT wordShingleMinHashUTF8(s) FROM defaults") + sys.stdout.write(res) + res = client.query("SELECT wordShingleMinHashCaseInsensitiveUTF8(s) FROM defaults") + sys.stdout.write(res) + + client.query("TRUNCATE TABLE defaults") + client.query("INSERT INTO defaults SELECT arrayJoin(splitByString('\n\n', 'ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency.\nClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. Downtime of a single node or the whole datacenter wont affect the systems availability for both reads and writes.\nClickHouse is simple and works out-of-the-box. It streamlines all your data processing: ingest all your structured data into the system and it becomes instantly available for building reports. SQL dialect allows expressing the desired result without involving any custom non-standard API that could be found in some alternative systems.\n\nClickHouse makes full use of all available hardware to process every request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (only used columns after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid single points of failure. Downtime for one site or the entire data center will not affect the system''s read and write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they immediately become available for building reports. The SQL dialect allows you to express the desired result without resorting to any non-standard APIs that can be found in some alternative systems.\n\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (used columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the system''s read / write availability.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they are immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.\n\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all of your structured data into the system, and it is immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.\n\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all your structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.\n\nClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency.\nClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system.\nClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.'))") + + res = client.query("SELECT 'uniqExact', uniqExact(s) FROM defaults") + sys.stdout.write(res) + + res = client.query("SELECT 'ngramSimHash'") + sys.stdout.write(res) + res = client.query("SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), ngramSimHash(s) as h FROM defaults GROUP BY h ORDER BY h") + sys.stdout.write(res) + res = client.query("SELECT 'ngramSimHashCaseInsensitive'") + sys.stdout.write(res) + res = client.query("SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), ngramSimHashCaseInsensitive(s) as h FROM defaults GROUP BY h ORDER BY h") + sys.stdout.write(res) + res = client.query("SELECT 'ngramSimHashUTF8'") + sys.stdout.write(res) + res = client.query("SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), ngramSimHashUTF8(s) as h FROM defaults GROUP BY h ORDER BY h") + sys.stdout.write(res) + res = client.query("SELECT 'ngramSimHashCaseInsensitiveUTF8'") + sys.stdout.write(res) + res = client.query("SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), ngramSimHashCaseInsensitiveUTF8(s) as h FROM defaults GROUP BY h ORDER BY h") + sys.stdout.write(res) + res = client.query("SELECT 'wordShingleSimHash'") + sys.stdout.write(res) + res = client.query("SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), wordShingleSimHash(s) as h FROM defaults GROUP BY h ORDER BY h") + sys.stdout.write(res) + res = client.query("SELECT 'wordShingleSimHashCaseInsensitive'") + sys.stdout.write(res) + res = client.query("SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), wordShingleSimHashCaseInsensitive(s) as h FROM defaults GROUP BY h ORDER BY h") + sys.stdout.write(res) + res = client.query("SELECT 'wordShingleSimHashUTF8'") + sys.stdout.write(res) + res = client.query("SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), wordShingleSimHashUTF8(s) as h FROM defaults GROUP BY h ORDER BY h") + sys.stdout.write(res) + res = client.query("SELECT 'wordShingleSimHashCaseInsensitiveUTF8'") + sys.stdout.write(res) + res = client.query("SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), wordShingleSimHashCaseInsensitiveUTF8(s) as h FROM defaults GROUP BY h ORDER BY h") + sys.stdout.write(res) + + res = client.query("SELECT 'ngramMinHash'") + sys.stdout.write(res) + res = client.query("SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), ngramMinHash(s) as h FROM defaults GROUP BY h ORDER BY h") + sys.stdout.write(res) + res = client.query("SELECT 'ngramMinHashCaseInsensitive'") + sys.stdout.write(res) + res = client.query("SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), ngramMinHashCaseInsensitive(s) as h FROM defaults GROUP BY h ORDER BY h") + sys.stdout.write(res) + res = client.query("SELECT 'ngramMinHashUTF8'") + sys.stdout.write(res) + res = client.query("SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), ngramMinHashUTF8(s) as h FROM defaults GROUP BY h ORDER BY h") + sys.stdout.write(res) + res = client.query("SELECT 'ngramMinHashCaseInsensitiveUTF8'") + sys.stdout.write(res) + res = client.query("SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), ngramMinHashCaseInsensitiveUTF8(s) as h FROM defaults GROUP BY h ORDER BY h") + sys.stdout.write(res) + res = client.query("SELECT 'wordShingleMinHash'") + sys.stdout.write(res) + res = client.query("SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), wordShingleMinHash(s) as h FROM defaults GROUP BY h ORDER BY h") + sys.stdout.write(res) + res = client.query("SELECT 'wordShingleMinHashCaseInsensitive'") + sys.stdout.write(res) + res = client.query("SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), wordShingleMinHashCaseInsensitive(s) as h FROM defaults GROUP BY h ORDER BY h") + sys.stdout.write(res) + res = client.query("SELECT 'wordShingleMinHashUTF8'") + sys.stdout.write(res) + res = client.query("SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), wordShingleMinHashUTF8(s) as h FROM defaults GROUP BY h ORDER BY h") + sys.stdout.write(res) + res = client.query("SELECT 'wordShingleMinHashCaseInsensitiveUTF8'") + sys.stdout.write(res) + res = client.query("SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), wordShingleMinHashCaseInsensitiveUTF8(s) as h FROM defaults GROUP BY h ORDER BY h") + sys.stdout.write(res) + + wordShingleSimHashInvalidArg1() + + wordShingleSimHashInvalidArg2() + + wordShingleSimHashInvalidArg3() + #client.query("DROP TABLE defaults") + +def wordShingleSimHashInvalidArg1(): + with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: + s.settimeout(30) + s.connect((CLICKHOUSE_HOST, CLICKHOUSE_PORT)) + sendHello(s) + receiveHello(s) + sendQuery(s, "SELECT wordShingleSimHash('foobar', 9223372036854775807)") + + # Fin block + sendEmptyBlock(s) + + + assertPacket(readVarUInt(s), 2) + print(readException(s)) + s.close() + + +def wordShingleSimHashInvalidArg2(): + with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: + s.settimeout(30) + s.connect((CLICKHOUSE_HOST, CLICKHOUSE_PORT)) + sendHello(s) + receiveHello(s) + sendQuery(s, "SELECT wordShingleSimHash('foobar', 1001)") + + # Fin block + sendEmptyBlock(s) + + assertPacket(readVarUInt(s), 2) + print(readException(s)) + s.close() + + +def wordShingleSimHashInvalidArg3(): + with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: + s.settimeout(30) + s.connect((CLICKHOUSE_HOST, CLICKHOUSE_PORT)) + sendHello(s) + receiveHello(s) + sendQuery(s, "SELECT wordShingleSimHash('foobar', 0)") + + # Fin block + sendEmptyBlock(s) + + assertPacket(readVarUInt(s), 2) + print(readException(s)) + s.close() + +if __name__ == "__main__": + test() + #wordShingleSimHashInvalidArg1() diff --git a/tests/queries/0_stateless/01016_simhash_minhash.sh b/tests/queries/0_stateless/01016_simhash_minhash.sh new file mode 100755 index 00000000000..94bac7efacb --- /dev/null +++ b/tests/queries/0_stateless/01016_simhash_minhash.sh @@ -0,0 +1,8 @@ +#!/usr/bin/env bash + +CURDIR=$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd) +# shellcheck source=../shell_config.sh +. "$CURDIR"/../shell_config.sh + +python3 "$CURDIR"/01016_simhash_minhash.python + diff --git a/tests/queries/0_stateless/01016_simhash_minhash.sql b/tests/queries/0_stateless/01016_simhash_minhash.sql deleted file mode 100644 index 1e77b487851..00000000000 --- a/tests/queries/0_stateless/01016_simhash_minhash.sql +++ /dev/null @@ -1,115 +0,0 @@ -SELECT ngramSimHash(''); -SELECT ngramSimHash('what a cute cat.'); -SELECT ngramSimHashCaseInsensitive('what a cute cat.'); -SELECT ngramSimHashUTF8('what a cute cat.'); -SELECT ngramSimHashCaseInsensitiveUTF8('what a cute cat.'); -SELECT wordShingleSimHash('what a cute cat.'); -SELECT wordShingleSimHashCaseInsensitive('what a cute cat.'); -SELECT wordShingleSimHashUTF8('what a cute cat.'); -SELECT wordShingleSimHashCaseInsensitiveUTF8('what a cute cat.'); - -SELECT ngramMinHash(''); -SELECT ngramMinHash('what a cute cat.'); -SELECT ngramMinHashCaseInsensitive('what a cute cat.'); -SELECT ngramMinHashUTF8('what a cute cat.'); -SELECT ngramMinHashCaseInsensitiveUTF8('what a cute cat.'); -SELECT wordShingleMinHash('what a cute cat.'); -SELECT wordShingleMinHashCaseInsensitive('what a cute cat.'); -SELECT wordShingleMinHashUTF8('what a cute cat.'); -SELECT wordShingleMinHashCaseInsensitiveUTF8('what a cute cat.'); - -DROP TABLE IF EXISTS defaults; -CREATE TABLE defaults -( - s String -)ENGINE = Memory(); - -INSERT INTO defaults values ('It is the latest occurrence of the Southeast European haze, the issue that occurs in constant intensity during every wet season. It has mainly been caused by forest fires resulting from illegal slash-and-burn clearing performed on behalf of the palm oil industry in Kazakhstan, principally on the islands, which then spread quickly in the dry season.') ('It is the latest occurrence of the Southeast Asian haze, the issue that occurs in constant intensity during every wet season. It has mainly been caused by forest fires resulting from illegal slash-and-burn clearing performed on behalf of the palm oil industry in Kazakhstan, principally on the islands, which then spread quickly in the dry season.'); - -SELECT ngramSimHash(s) FROM defaults; -SELECT ngramSimHashCaseInsensitive(s) FROM defaults; -SELECT ngramSimHashUTF8(s) FROM defaults; -SELECT ngramSimHashCaseInsensitiveUTF8(s) FROM defaults; -SELECT wordShingleSimHash(s) FROM defaults; -SELECT wordShingleSimHashCaseInsensitive(s) FROM defaults; -SELECT wordShingleSimHashUTF8(s) FROM defaults; -SELECT wordShingleSimHashCaseInsensitiveUTF8(s) FROM defaults; - -SELECT ngramMinHash(s) FROM defaults; -SELECT ngramMinHashCaseInsensitive(s) FROM defaults; -SELECT ngramMinHashUTF8(s) FROM defaults; -SELECT ngramMinHashCaseInsensitiveUTF8(s) FROM defaults; -SELECT wordShingleMinHash(s) FROM defaults; -SELECT wordShingleMinHashCaseInsensitive(s) FROM defaults; -SELECT wordShingleMinHashUTF8(s) FROM defaults; -SELECT wordShingleMinHashCaseInsensitiveUTF8(s) FROM defaults; - -TRUNCATE TABLE defaults; -INSERT INTO defaults SELECT arrayJoin(splitByString('\n\n', -'ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency. -ClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure. Downtime of a single node or the whole datacenter wont affect the systems availability for both reads and writes. -ClickHouse is simple and works out-of-the-box. It streamlines all your data processing: ingest all your structured data into the system and it becomes instantly available for building reports. SQL dialect allows expressing the desired result without involving any custom non-standard API that could be found in some alternative systems. - -ClickHouse makes full use of all available hardware to process every request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (only used columns after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency. -ClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid single points of failure. Downtime for one site or the entire data center will not affect the system''s read and write availability. -ClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they immediately become available for building reports. The SQL dialect allows you to express the desired result without resorting to any non-standard APIs that can be found in some alternative systems. - -ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (used columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency. -ClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the system''s read / write availability. -ClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all your structured data into the system, and they are immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. - -ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns only after unpacking). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency. -ClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system. -ClickHouse is simple and works out of the box. It simplifies all the processing of your data: it loads all of your structured data into the system, and it is immediately available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. - -ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency. -ClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system. -ClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all your structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems. - -ClickHouse makes full use of all available hardware to process each request as quickly as possible. Peak performance for a single query is over 2 terabytes per second (using columns after decompression only). In a distributed setup, reads are automatically balanced across healthy replicas to avoid increased latency. -ClickHouse supports asynchronous multi-master replication and can be deployed across multiple data centers. All nodes are equal to avoid a single point of failure. Downtime for one site or the entire data center will not affect the read / write availability of the system. -ClickHouse is simple and works out of the box. It simplifies all processing of your data: it loads all structured data into the system and immediately becomes available for building reports. The SQL dialect allows you to express the desired result without resorting to any of the non-standard APIs found in some alternative systems.' -)); - -SELECT 'uniqExact', uniqExact(s) FROM defaults; - - -SELECT 'ngramSimHash'; -SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), ngramSimHash(s) as h FROM defaults GROUP BY h ORDER BY h; -SELECT 'ngramSimHashCaseInsensitive'; -SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), ngramSimHashCaseInsensitive(s) as h FROM defaults GROUP BY h ORDER BY h; -SELECT 'ngramSimHashUTF8'; -SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), ngramSimHashUTF8(s) as h FROM defaults GROUP BY h ORDER BY h; -SELECT 'ngramSimHashCaseInsensitiveUTF8'; -SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), ngramSimHashCaseInsensitiveUTF8(s) as h FROM defaults GROUP BY h ORDER BY h; -SELECT 'wordShingleSimHash'; -SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), wordShingleSimHash(s, 2) as h FROM defaults GROUP BY h ORDER BY h; -SELECT 'wordShingleSimHashCaseInsensitive'; -SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), wordShingleSimHashCaseInsensitive(s, 2) as h FROM defaults GROUP BY h ORDER BY h; -SELECT 'wordShingleSimHashUTF8'; -SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), wordShingleSimHashUTF8(s, 2) as h FROM defaults GROUP BY h ORDER BY h; -SELECT 'wordShingleSimHashCaseInsensitiveUTF8'; -SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), wordShingleSimHashCaseInsensitiveUTF8(s, 2) as h FROM defaults GROUP BY h ORDER BY h; - -SELECT 'ngramMinHash'; -SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), ngramMinHash(s) as h FROM defaults GROUP BY h ORDER BY h; -SELECT 'ngramMinHashCaseInsensitive'; -SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), ngramMinHashCaseInsensitive(s) as h FROM defaults GROUP BY h ORDER BY h; -SELECT 'ngramMinHashUTF8'; -SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), ngramMinHashUTF8(s) as h FROM defaults GROUP BY h ORDER BY h; -SELECT 'ngramMinHashCaseInsensitiveUTF8'; -SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), ngramMinHashCaseInsensitiveUTF8(s) as h FROM defaults GROUP BY h ORDER BY h; -SELECT 'wordShingleMinHash'; -SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), wordShingleMinHash(s, 2, 3) as h FROM defaults GROUP BY h ORDER BY h; -SELECT 'wordShingleMinHashCaseInsensitive'; -SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), wordShingleMinHashCaseInsensitive(s, 2, 3) as h FROM defaults GROUP BY h ORDER BY h; -SELECT 'wordShingleMinHashUTF8'; -SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), wordShingleMinHashUTF8(s, 2, 3) as h FROM defaults GROUP BY h ORDER BY h; -SELECT 'wordShingleMinHashCaseInsensitiveUTF8'; -SELECT arrayStringConcat(groupArray(s), '\n:::::::\n'), count(), wordShingleMinHashCaseInsensitiveUTF8(s, 2, 3) as h FROM defaults GROUP BY h ORDER BY h; - -SELECT wordShingleSimHash('foobar', 9223372036854775807); -- { serverError 69 } -SELECT wordShingleSimHash('foobar', 1001); -- { serverError 69 } -SELECT wordShingleSimHash('foobar', 0); -- { serverError 69 } - -DROP TABLE defaults; diff --git a/tests/queries/0_stateless/01016_simhash_minhash.reference b/tests/queries/0_stateless/01016_simhash_minhash.x86_64.reference similarity index 100% rename from tests/queries/0_stateless/01016_simhash_minhash.reference rename to tests/queries/0_stateless/01016_simhash_minhash.x86_64.reference