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234 lines
11 KiB
Markdown
234 lines
11 KiB
Markdown
---
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slug: /en/engines/table-engines/integrations/hdfs
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sidebar_position: 6
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sidebar_label: HDFS
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---
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# HDFS
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This engine provides integration with the [Apache Hadoop](https://en.wikipedia.org/wiki/Apache_Hadoop) ecosystem by allowing to manage data on [HDFS](https://hadoop.apache.org/docs/current/hadoop-project-dist/hadoop-hdfs/HdfsDesign.html) via ClickHouse. This engine is similar to the [File](../../../engines/table-engines/special/file.md#table_engines-file) and [URL](../../../engines/table-engines/special/url.md#table_engines-url) engines, but provides Hadoop-specific features.
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## Usage {#usage}
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``` sql
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ENGINE = HDFS(URI, format)
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```
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**Engine Parameters**
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- `URI` - whole file URI in HDFS. The path part of `URI` may contain globs. In this case the table would be readonly.
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- `format` - specifies one of the available file formats. To perform
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`SELECT` queries, the format must be supported for input, and to perform
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`INSERT` queries – for output. The available formats are listed in the
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[Formats](../../../interfaces/formats.md#formats) section.
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**Example:**
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**1.** Set up the `hdfs_engine_table` table:
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``` sql
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CREATE TABLE hdfs_engine_table (name String, value UInt32) ENGINE=HDFS('hdfs://hdfs1:9000/other_storage', 'TSV')
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```
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**2.** Fill file:
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``` sql
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INSERT INTO hdfs_engine_table VALUES ('one', 1), ('two', 2), ('three', 3)
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```
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**3.** Query the data:
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``` sql
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SELECT * FROM hdfs_engine_table LIMIT 2
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```
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``` text
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┌─name─┬─value─┐
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│ one │ 1 │
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│ two │ 2 │
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└──────┴───────┘
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```
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## Implementation Details {#implementation-details}
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- Reads and writes can be parallel.
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- Not supported:
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- `ALTER` and `SELECT...SAMPLE` operations.
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- Indexes.
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- [Zero-copy](../../../operations/storing-data.md#zero-copy) replication is possible, but not recommended.
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:::warning Zero-copy replication is not ready for production
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Zero-copy replication is disabled by default in ClickHouse version 22.8 and higher. This feature is not recommended for production use.
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:::
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**Globs in path**
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Multiple path components can have globs. For being processed file should exists and matches to the whole path pattern. Listing of files determines during `SELECT` (not at `CREATE` moment).
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- `*` — Substitutes any number of any characters except `/` including empty string.
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- `?` — Substitutes any single character.
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- `{some_string,another_string,yet_another_one}` — Substitutes any of strings `'some_string', 'another_string', 'yet_another_one'`.
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- `{N..M}` — Substitutes any number in range from N to M including both borders.
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Constructions with `{}` are similar to the [remote](../../../sql-reference/table-functions/remote.md) table function.
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**Example**
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1. Suppose we have several files in TSV format with the following URIs on HDFS:
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- 'hdfs://hdfs1:9000/some_dir/some_file_1'
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- 'hdfs://hdfs1:9000/some_dir/some_file_2'
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- 'hdfs://hdfs1:9000/some_dir/some_file_3'
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- 'hdfs://hdfs1:9000/another_dir/some_file_1'
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- 'hdfs://hdfs1:9000/another_dir/some_file_2'
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- 'hdfs://hdfs1:9000/another_dir/some_file_3'
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1. There are several ways to make a table consisting of all six files:
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<!-- -->
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``` sql
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CREATE TABLE table_with_range (name String, value UInt32) ENGINE = HDFS('hdfs://hdfs1:9000/{some,another}_dir/some_file_{1..3}', 'TSV')
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```
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Another way:
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``` sql
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CREATE TABLE table_with_question_mark (name String, value UInt32) ENGINE = HDFS('hdfs://hdfs1:9000/{some,another}_dir/some_file_?', 'TSV')
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```
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Table consists of all the files in both directories (all files should satisfy format and schema described in query):
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``` sql
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CREATE TABLE table_with_asterisk (name String, value UInt32) ENGINE = HDFS('hdfs://hdfs1:9000/{some,another}_dir/*', 'TSV')
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```
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:::warning
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If the listing of files contains number ranges with leading zeros, use the construction with braces for each digit separately or use `?`.
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:::
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**Example**
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Create table with files named `file000`, `file001`, … , `file999`:
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``` sql
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CREATE TABLE big_table (name String, value UInt32) ENGINE = HDFS('hdfs://hdfs1:9000/big_dir/file{0..9}{0..9}{0..9}', 'CSV')
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```
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## Configuration {#configuration}
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Similar to GraphiteMergeTree, the HDFS engine supports extended configuration using the ClickHouse config file. There are two configuration keys that you can use: global (`hdfs`) and user-level (`hdfs_*`). The global configuration is applied first, and then the user-level configuration is applied (if it exists).
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``` xml
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<!-- Global configuration options for HDFS engine type -->
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<hdfs>
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<hadoop_kerberos_keytab>/tmp/keytab/clickhouse.keytab</hadoop_kerberos_keytab>
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<hadoop_kerberos_principal>clickuser@TEST.CLICKHOUSE.TECH</hadoop_kerberos_principal>
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<hadoop_security_authentication>kerberos</hadoop_security_authentication>
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</hdfs>
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<!-- Configuration specific for user "root" -->
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<hdfs_root>
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<hadoop_kerberos_principal>root@TEST.CLICKHOUSE.TECH</hadoop_kerberos_principal>
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</hdfs_root>
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```
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### Configuration Options {#configuration-options}
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#### Supported by libhdfs3 {#supported-by-libhdfs3}
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| **parameter** | **default value** |
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| - | - |
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| rpc\_client\_connect\_tcpnodelay | true |
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| dfs\_client\_read\_shortcircuit | true |
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| output\_replace-datanode-on-failure | true |
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| input\_notretry-another-node | false |
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| input\_localread\_mappedfile | true |
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| dfs\_client\_use\_legacy\_blockreader\_local | false |
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| rpc\_client\_ping\_interval | 10 * 1000 |
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| rpc\_client\_connect\_timeout | 600 * 1000 |
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| rpc\_client\_read\_timeout | 3600 * 1000 |
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| rpc\_client\_write\_timeout | 3600 * 1000 |
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| rpc\_client\_socekt\_linger\_timeout | -1 |
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| rpc\_client\_connect\_retry | 10 |
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| rpc\_client\_timeout | 3600 * 1000 |
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| dfs\_default\_replica | 3 |
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| input\_connect\_timeout | 600 * 1000 |
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| input\_read\_timeout | 3600 * 1000 |
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| input\_write\_timeout | 3600 * 1000 |
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| input\_localread\_default\_buffersize | 1 * 1024 * 1024 |
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| dfs\_prefetchsize | 10 |
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| input\_read\_getblockinfo\_retry | 3 |
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| input\_localread\_blockinfo\_cachesize | 1000 |
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| input\_read\_max\_retry | 60 |
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| output\_default\_chunksize | 512 |
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| output\_default\_packetsize | 64 * 1024 |
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| output\_default\_write\_retry | 10 |
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| output\_connect\_timeout | 600 * 1000 |
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| output\_read\_timeout | 3600 * 1000 |
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| output\_write\_timeout | 3600 * 1000 |
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| output\_close\_timeout | 3600 * 1000 |
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| output\_packetpool\_size | 1024 |
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| output\_heeartbeat\_interval | 10 * 1000 |
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| dfs\_client\_failover\_max\_attempts | 15 |
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| dfs\_client\_read\_shortcircuit\_streams\_cache\_size | 256 |
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| dfs\_client\_socketcache\_expiryMsec | 3000 |
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| dfs\_client\_socketcache\_capacity | 16 |
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| dfs\_default\_blocksize | 64 * 1024 * 1024 |
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| dfs\_default\_uri | "hdfs://localhost:9000" |
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| hadoop\_security\_authentication | "simple" |
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| hadoop\_security\_kerberos\_ticket\_cache\_path | "" |
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| dfs\_client\_log\_severity | "INFO" |
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| dfs\_domain\_socket\_path | "" |
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[HDFS Configuration Reference](https://hawq.apache.org/docs/userguide/2.3.0.0-incubating/reference/HDFSConfigurationParameterReference.html) might explain some parameters.
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#### ClickHouse extras {#clickhouse-extras}
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| **parameter** | **default value** |
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| - | - |
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|hadoop\_kerberos\_keytab | "" |
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|hadoop\_kerberos\_principal | "" |
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|libhdfs3\_conf | "" |
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### Limitations {#limitations}
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* `hadoop_security_kerberos_ticket_cache_path` and `libhdfs3_conf` can be global only, not user specific
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## Kerberos support {#kerberos-support}
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If the `hadoop_security_authentication` parameter has the value `kerberos`, ClickHouse authenticates via Kerberos.
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Parameters are [here](#clickhouse-extras) and `hadoop_security_kerberos_ticket_cache_path` may be of help.
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Note that due to libhdfs3 limitations only old-fashioned approach is supported,
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datanode communications are not secured by SASL (`HADOOP_SECURE_DN_USER` is a reliable indicator of such
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security approach). Use `tests/integration/test_storage_kerberized_hdfs/hdfs_configs/bootstrap.sh` for reference.
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If `hadoop_kerberos_keytab`, `hadoop_kerberos_principal` or `hadoop_security_kerberos_ticket_cache_path` are specified, Kerberos authentication will be used. `hadoop_kerberos_keytab` and `hadoop_kerberos_principal` are mandatory in this case.
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## HDFS Namenode HA support {#namenode-ha}
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libhdfs3 support HDFS namenode HA.
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- Copy `hdfs-site.xml` from an HDFS node to `/etc/clickhouse-server/`.
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- Add following piece to ClickHouse config file:
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``` xml
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<hdfs>
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<libhdfs3_conf>/etc/clickhouse-server/hdfs-site.xml</libhdfs3_conf>
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</hdfs>
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```
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- Then use `dfs.nameservices` tag value of `hdfs-site.xml` as the namenode address in the HDFS URI. For example, replace `hdfs://appadmin@192.168.101.11:8020/abc/` with `hdfs://appadmin@my_nameservice/abc/`.
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## Virtual Columns {#virtual-columns}
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- `_path` — Path to the file.
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- `_file` — Name of the file.
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**See Also**
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- [Virtual columns](../../../engines/table-engines/index.md#table_engines-virtual_columns)
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[Original article](https://clickhouse.com/docs/en/engines/table-engines/integrations/hdfs/) <!--hide-->
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