2020-04-08 14:22:25 +00:00
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---
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machine_translated: true
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2020-05-15 04:34:54 +00:00
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machine_translated_rev: 72537a2d527c63c07aa5d2361a8829f3895cf2bd
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2020-04-08 14:22:25 +00:00
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toc_priority: 36
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toc_title: HDFS
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---
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# HDFS {#table_engines-hdfs}
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该引擎提供了集成 [Apache Hadoop](https://en.wikipedia.org/wiki/Apache_Hadoop) 生态系统通过允许管理数据 [HDFS](https://hadoop.apache.org/docs/current/hadoop-project-dist/hadoop-hdfs/HdfsDesign.html)通过ClickHouse. 这个引擎是相似的
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2020-05-06 06:13:29 +00:00
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到 [文件](../special/file.md#table_engines-file) 和 [URL](../special/url.md#table_engines-url) 引擎,但提供Hadoop特定的功能。
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2020-04-08 14:22:25 +00:00
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## 用途 {#usage}
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``` sql
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ENGINE = HDFS(URI, format)
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```
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该 `URI` 参数是HDFS中的整个文件URI。
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该 `format` 参数指定一种可用的文件格式。 执行
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`SELECT` 查询时,格式必须支持输入,并执行
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`INSERT` queries – for output. The available formats are listed in the
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[格式](../../../interfaces/formats.md#formats) 科。
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路径部分 `URI` 可能包含水珠。 在这种情况下,表将是只读的。
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**示例:**
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**1.** 设置 `hdfs_engine_table` 表:
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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.** 填充文件:
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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.** 查询数据:
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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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## 实施细节 {#implementation-details}
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- 读取和写入可以并行
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- 不支持:
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- `ALTER` 和 `SELECT...SAMPLE` 操作。
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- 索引。
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- 复制。
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**路径中的水珠**
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多个路径组件可以具有globs。 对于正在处理的文件应该存在并匹配到整个路径模式。 文件列表确定在 `SELECT` (不在 `CREATE` 时刻)。
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- `*` — Substitutes any number of any characters except `/` 包括空字符串。
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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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2020-04-30 18:19:18 +00:00
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建筑与 `{}` 类似于 [远程](../../../sql-reference/table-functions/remote.md) 表功能。
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2020-04-08 14:22:25 +00:00
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**示例**
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1. 假设我们在HDFS上有几个TSV格式的文件,其中包含以下Uri:
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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. 有几种方法可以创建由所有六个文件组成的表:
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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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另一种方式:
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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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表由两个目录中的所有文件组成(所有文件都应满足query中描述的格式和模式):
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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 "警告"
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如果文件列表包含带有前导零的数字范围,请单独使用带有大括号的构造或使用 `?`.
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**示例**
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创建具有名为文件的表 `file000`, `file001`, … , `file999`:
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``` sql
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CREARE 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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## 虚拟列 {#virtual-columns}
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- `_path` — Path to the file.
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- `_file` — Name of the file.
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**另请参阅**
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- [虚拟列](../index.md#table_engines-virtual_columns)
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[原始文章](https://clickhouse.tech/docs/en/operations/table_engines/hdfs/) <!--hide-->
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