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hdfs

Creates a table from files in HDFS. This table function is similar to url and file ones.

hdfs(URI, format, structure)

Input parameters

  • URI — The relative URI to the file in HDFS. Path to file support following globs in readonly mode: *, ?, {abc,def} and {N..M} where N, M — numbers, `'abc', 'def' — strings.
  • format — The format of the file.
  • structure — Structure of the table. Format 'column1_name column1_type, column2_name column2_type, ...'.

Returned value

A table with the specified structure for reading or writing data in the specified file.

Example

Table from hdfs://hdfs1:9000/test and selection of the first two rows from it:

SELECT *
FROM hdfs('hdfs://hdfs1:9000/test', 'TSV', 'column1 UInt32, column2 UInt32, column3 UInt32')
LIMIT 2
┌─column1─┬─column2─┬─column3─┐
│       1 │       2 │       3 │
│       3 │       2 │       1 │
└─────────┴─────────┴─────────┘

Globs in path​

Paths may use globbing. Files must match the whole path pattern, not only the suffix or prefix.

  • * — Represents arbitrarily many characters except / but including the empty string.
  • ** — Represents all files inside a folder recursively.
  • ? — Represents an arbitrary single character.
  • {some_string,another_string,yet_another_one} — Substitutes any of strings 'some_string', 'another_string', 'yet_another_one'. The strings can contain the / symbol.
  • {N..M} — Represents any number >= N and <= M.

Constructions with {} are similar to the remote and file table functions.

Example

  1. Suppose that we have several files with following URIs on HDFS:
  • ‘hdfs://hdfs1:9000/some_dir/some_file_1’
  • ‘hdfs://hdfs1:9000/some_dir/some_file_2’
  • ‘hdfs://hdfs1:9000/some_dir/some_file_3’
  • ‘hdfs://hdfs1:9000/another_dir/some_file_1’
  • ‘hdfs://hdfs1:9000/another_dir/some_file_2’
  • ‘hdfs://hdfs1:9000/another_dir/some_file_3’
  1. Query the amount of rows in these files:
SELECT count(*)
FROM hdfs('hdfs://hdfs1:9000/{some,another}_dir/some_file_{1..3}', 'TSV', 'name String, value UInt32')
  1. Query the amount of rows in all files of these two directories:
SELECT count(*)
FROM hdfs('hdfs://hdfs1:9000/{some,another}_dir/*', 'TSV', 'name String, value UInt32')
Note

If your listing of files contains number ranges with leading zeros, use the construction with braces for each digit separately or use ?.

Example

Query the data from files named file000, file001, ... , file999:

SELECT count(*)
FROM hdfs('hdfs://hdfs1:9000/big_dir/file{0..9}{0..9}{0..9}', 'CSV', 'name String, value UInt32')

Virtual Columns​

  • _path — Path to the file. Type: LowCardinalty(String).
  • _file — Name of the file. Type: LowCardinalty(String).
  • _size — Size of the file in bytes. Type: Nullable(UInt64). If the size is unknown, the value is NULL.
  • _time — Last modified time of the file. Type: Nullable(DateTime). If the time is unknown, the value is NULL.

Hive-style partitioning​

When setting use_hive_partitioning is set to 1, ClickHouse will detect Hive-style partitioning in the path (/name=value/) and will allow to use partition columns as virtual columns in the query. These virtual columns will have the same names as in the partitioned path, but starting with _.

Example

Use virtual column, created with Hive-style partitioning

SET use_hive_partitioning = 1;
SELECT * from HDFS('hdfs://hdfs1:9000/data/path/date=*/country=*/code=*/*.parquet') where _date > '2020-01-01' and _country = 'Netherlands' and _code = 42;

Storage Settings​

See Also