HDFS

HDFS

Name

hdfs

Description

HDFS table-valued-function(tvf), allows users to read and access file contents on S3-compatible object storage, just like accessing relational table. Currently supports csv/csv_with_names/csv_with_names_and_types/json/parquet/orc file format.

syntax

hdfs(
  "uri" = "..",
  "fs.defaultFS" = "...",
  "hadoop.username" = "...",
  "format" = "csv",
  "keyn" = "valuen" 
  ...
  );

parameter description

Related parameters for accessing hdfs:

• uri: (required) hdfs uri. If the uri path does not exist or the files are empty files, hdfs tvf will return an empty result set.
• fs.defaultFS: (required)
• hadoop.username: (required) Can be any string, but cannot be empty.
• hadoop.security.authentication: (optional)
• hadoop.username: (optional)
• hadoop.kerberos.principal: (optional)
• hadoop.kerberos.keytab: (optional)
• dfs.client.read.shortcircuit: (optional)
• dfs.domain.socket.path: (optional)

Related parameters for accessing HDFS in HA mode:

• dfs.nameservices: (optional)
• dfs.ha.namenodes.your-nameservices: (optional)
• dfs.namenode.rpc-address.your-nameservices.your-namenode: (optional)
• dfs.client.failover.proxy.provider.your-nameservices: (optional)

File format parameters:

• format: (required) Currently support csv/csv_with_names/csv_with_names_and_types/json/parquet/orc/avro

• column_separator: (optional) default \t.

• line_delimiter: (optional) default \n.

• compress_type: (optional) Currently support UNKNOWN/PLAIN/GZ/LZO/BZ2/LZ4FRAME/DEFLATE/SNAPPYBLOCK. Default value is UNKNOWN, it will automatically infer the type based on the suffix of uri.

  The following 6 parameters are used for loading in json format. For specific usage methods, please refer to: Json Load

• read_json_by_line: (optional) default "true"

• strip_outer_array: (optional) default "false"

• json_root: (optional) default ""

• json_paths: (optional) default ""

• num_as_string: (optional) default false

• fuzzy_parse: (optional) default false

  The following 2 parameters are used for loading in csv format:

• trim_double_quotes: Boolean type (optional), the default value is false. True means that the outermost double quotes of each field in the csv file are trimmed.

• skip_lines: Integer type (optional), the default value is 0. It will skip some lines in the head of csv file. It will be disabled when the format is csv_with_names or csv_with_names_and_types.

other kinds of parameters:

• path_partition_keys: (optional) Specifies the column names carried in the file path. For example, if the file path is /path/to/city=beijing/date="2023-07-09", you should fill in path_partition_keys="city,date". It will automatically read the corresponding column names and values from the path during load process.
• resource：（optional）Specify the resource name. Hdfs Tvf can use the existing Hdfs resource to directly access Hdfs. You can refer to the method for creating an Hdfs resource: CREATE-RESOURCE. This property is supported starting from version 2.1.4.

Tip

To directly query a TVF or create a VIEW based on that TVF, you need to have usage permission for that resource. To query a VIEW created based on TVF, you only need select permission for that VIEW.

Examples

Read and access csv format files on hdfs storage.

MySQL [(none)]> select * from hdfs(
            "uri" = "hdfs://127.0.0.1:842/user/doris/csv_format_test/student.csv",
            "fs.defaultFS" = "hdfs://127.0.0.1:8424",
            "hadoop.username" = "doris",
            "format" = "csv");
+------+---------+------+
| c1   | c2      | c3   |
+------+---------+------+
| 1    | alice   | 18   |
| 2    | bob     | 20   |
| 3    | jack    | 24   |
| 4    | jackson | 19   |
| 5    | liming  | 18   |
+------+---------+------+

Read and access csv format files on hdfs storage in HA mode.

MySQL [(none)]> select * from hdfs(
            "uri" = "hdfs://127.0.0.1:842/user/doris/csv_format_test/student.csv",
            "fs.defaultFS" = "hdfs://127.0.0.1:8424",
            "hadoop.username" = "doris",
            "format" = "csv",
            "dfs.nameservices" = "my_hdfs",
            "dfs.ha.namenodes.my_hdfs" = "nn1,nn2",
            "dfs.namenode.rpc-address.my_hdfs.nn1" = "nanmenode01:8020",
            "dfs.namenode.rpc-address.my_hdfs.nn2" = "nanmenode02:8020",
            "dfs.client.failover.proxy.provider.my_hdfs" = "org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider");
+------+---------+------+
| c1   | c2      | c3   |
+------+---------+------+
| 1    | alice   | 18   |
| 2    | bob     | 20   |
| 3    | jack    | 24   |
| 4    | jackson | 19   |
| 5    | liming  | 18   |
+------+---------+------+

Can be used with desc function :

MySQL [(none)]> desc function hdfs(
            "uri" = "hdfs://127.0.0.1:8424/user/doris/csv_format_test/student_with_names.csv",
            "fs.defaultFS" = "hdfs://127.0.0.1:8424",
            "hadoop.username" = "doris",
            "format" = "csv_with_names");

Keywords

hdfs, table-valued-function, tvf

Best Practice

For more detailed usage of HDFS tvf, please refer to S3 tvf, The only difference between them is the way of accessing the storage system.