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ClickHouse® is a real-time analytics DBMS
00fdfa115f
NgramDistanceImpl::unrollLowering() relies on the fact that PODArray has
padding and it is OK to access more items.
Here is an MSan report:
==656==WARNING: MemorySanitizer: use-of-uninitialized-value
0 0x557fd825485f in DB::NgramDistanceImpl<4ul, char8_t, false, true, false>::vectorConstant(DB::PODArray<char8_t, 4096ul, Allocator<false, false>, 63ul, 64ul> const&, DB::PODArray<unsigned long, 4096ul, Allocator<false, false>, 63ul, 64ul> const&, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, DB::PODArray<float, 4096ul, Allocator<false, false>, 63ul, 64ul>&) (/usr/bin/clickhouse+0x124d885f) (BuildId: 76773125d8739591c75d4f4d263a2ffe7ca96855)
1 0x557fd824eb83 in DB::FunctionsStringSimilarity<DB::NgramDistanceImpl<4ul, char8_t, false, true, false>, DB::NameNgramSearchCaseInsensitive>::executeImpl(std::__1::vector<DB::ColumnWithTypeAndName, std::__1::allocator<DB::ColumnWithTypeAndName>> const&, std::__1::shared_ptr<DB::IDataType const> const&, unsigned long) const (/usr/bin/clickhouse+0x124d2b83) (BuildId: 76773125d8739591c75d4f4d263a2ffe7ca96855)
2 0x557fd50023b7 in DB::FunctionToExecutableFunctionAdaptor::executeImpl() const (/usr/bin/clickhouse+0xf2863b7) (BuildId: 76773125d8739591c75d4f4d263a2ffe7ca96855)
Uninitialized value was stored to memory at
0 0x557fd4f8da5a in __msan_memcpy (/usr/bin/clickhouse+0xf211a5a) (BuildId: 76773125d8739591c75d4f4d263a2ffe7ca96855)
1 0x557fd8253803 in DB::NgramDistanceImpl<4ul, char8_t, false, true, false>::vectorConstant(DB::PODArray<char8_t, 4096ul, Allocator<false, false>, 63ul, 64ul> const&, DB::PODArray<unsigned long, 4096ul, Allocator<false, false>, 63ul, 64ul> const&, std::__1::basic_string<char, std::__1::char_traits<char>, std::__1::allocator<char>>, DB::PODArray<float, 4096ul, Allocator<false, false>, 63ul, 64ul>&) (/usr/bin/clickhouse+0x124d7803) (BuildId: 76773125d8739591c75d4f4d263a2ffe7ca96855)
2 0x557fd824eb83 in DB::FunctionsStringSimilarity<DB::NgramDistanceImpl<4ul, char8_t, false, true, false>, DB::NameNgramSearchCaseInsensitive>::executeImpl(std::__1::vector<DB::ColumnWithTypeAndName, std::__1::allocator<DB::ColumnWithTypeAndName>> const&, std::__1::shared_ptr<DB::IDataType const> const&, unsigned long) const (/usr/bin/clickhouse+0x124d2b83) (BuildId: 76773125d8739591c75d4f4d263a2ffe7ca96855)
3 0x557fd50023b7 in DB::FunctionToExecutableFunctionAdaptor::executeImpl() const (/usr/bin/clickhouse+0xf2863b7) (BuildId: 76773125d8739591c75d4f4d263a2ffe7ca96855)
Uninitialized value was stored to memory at
0 0x557fd4f8da5a in __msan_memcpy (/usr/bin/clickhouse+0xf211a5a) (BuildId: 76773125d8739591c75d4f4d263a2ffe7ca96855)
1 0x5580061699f5 in detail::memcpySmallAllowReadWriteOverflow15Impl(char*, char const*, long) build_docker/./src/Common/memcpySmall.h:42:13
2 0x5580061699f5 in memcpySmallAllowReadWriteOverflow15(void*, void const*, unsigned long) build_docker/./src/Common/memcpySmall.h:57:5
3 0x5580061699f5 in DB::ColumnString::replicate(DB::PODArray<unsigned long, 4096ul, Allocator<false, false>, 63ul, 64ul> const&) const build_docker/./src/Columns/ColumnString.cpp:462:13
4 0x558005d3fae4 in DB::ColumnConst::convertToFullColumn() const build_docker/./src/Columns/ColumnConst.cpp:48:18
Signed-off-by: Azat Khuzhin <a.khuzhin@semrush.com>
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| src | ||
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| utils | ||
| .clang-format | ||
| .clang-tidy | ||
| .editorconfig | ||
| .exrc | ||
| .git-blame-ignore-revs | ||
| .gitattributes | ||
| .gitignore | ||
| .gitmodules | ||
| .pylintrc | ||
| .snyk | ||
| .yamllint | ||
| AUTHORS | ||
| CHANGELOG.md | ||
| CMakeLists.txt | ||
| CODE_OF_CONDUCT.md | ||
| CONTRIBUTING.md | ||
| format_sources | ||
| LICENSE | ||
| PreLoad.cmake | ||
| README.md | ||
| SECURITY.md | ||
ClickHouse® is an open-source column-oriented database management system that allows generating analytical data reports in real-time.
How To Install (Linux, macOS, FreeBSD)
curl https://clickhouse.com/ | sh
Useful Links
- Official website has a quick high-level overview of ClickHouse on the main page.
- ClickHouse Cloud ClickHouse as a service, built by the creators and maintainers.
- Tutorial shows how to set up and query a small ClickHouse cluster.
- Documentation provides more in-depth information.
- YouTube channel has a lot of content about ClickHouse in video format.
- Slack and Telegram allow chatting with ClickHouse users in real-time.
- Blog contains various ClickHouse-related articles, as well as announcements and reports about events.
- Code Browser (Woboq) with syntax highlight and navigation.
- Code Browser (github.dev) with syntax highlight, powered by github.dev.
- Contacts can help to get your questions answered if there are any.
Upcoming Events
- v23.4 Release Webinar - April 26 - 23.4 is rapidly approaching. Original creator, co-founder, and CTO of ClickHouse Alexey Milovidov will walk us through the highlights of the release.
- ClickHouse Meetup in Berlin - May 16
- ClickHouse Meetup in Barcelona - May 25
- ClickHouse Meetup in London - May 25
- ClickHouse Meetup in San Francisco - Jun 7
- ClickHouse Meetup in Stockholm - Jun 13
Also, keep an eye out for upcoming meetups in Amsterdam, Boston, NYC, Beijing, and Toronto. Somewhere else you want us to be? Please feel free to reach out to tyler clickhouse com.
Recent Recordings
- Recent Meetup Videos: Meetup Playlist Whenever possible recordings of the ClickHouse Community Meetups are edited and presented as individual talks. Current featuring "Modern SQL in 2023", "Fast, Concurrent, and Consistent Asynchronous INSERTS in ClickHouse", and "Full-Text Indices: Design and Experiments"
- Recording available: v23.4 Release Webinar UNDROP TABLE, server settings introspection, nested dynamic disks, MySQL compatibility, parseDate Time, Lightweight Deletes, Parallel Replicas, integrations updates, and so much more! Watch it now!
- All release webinar recordings: YouTube playlist