Accessing Hadoop with PXF
PXF is compatible with Cloudera, Hortonworks Data Platform, MapR, and generic Apache Hadoop distributions. PXF is installed with HDFS, Hive, and HBase connectors. You use these connectors to access varied formats of data from these Hadoop distributions.
HDFS is the primary distributed storage mechanism used by Apache Hadoop. When a user or application performs a query on a PXF external table that references an HDFS file, the Greenplum Database master node dispatches the query to all segment hosts. Each segment instance contacts the PXF agent running on its host. When it receives the request from a segment instance, the PXF agent:
- Allocates a worker thread to serve the request from a segment.
- Invokes the HDFS Java API to request metadata information for the HDFS file from the HDFS NameNode.
- Provides the metadata information returned by the HDFS NameNode to the segment instance.
Figure: PXF-to-Hadoop Architecture
A segment instance uses its Greenplum Database
gp_segment_id and the file block information described in the metadata to assign itself a specific portion of the query data. The segment instance then sends a request to the PXF agent to read the assigned data. This data may reside on one or more HDFS DataNodes.
The PXF agent invokes the HDFS Java API to read the data and delivers it to the segment instance. The segment instance delivers its portion of the data to the Greenplum Database master node. This communication occurs across segment hosts and segment instances in parallel.
Before working with Hadoop data using PXF, ensure that:
- You have configured and initialized PXF, and PXF is running on each Greenplum Database segment host. See Configuring PXF for additional information.
- You have configured the PXF Hadoop Connectors that you plan to use. Refer to Configuring PXF Hadoop Connectors for instructions. If you plan to access JSON-formatted data stored in a Cloudera Hadoop cluster, PXF requires a Cloudera version 5.8 or later Hadoop distribution.
- If user impersonation is enabled (the default), ensure that you have granted read (and write as appropriate) permission to the HDFS files and directories that will be accessed as external tables in Greenplum Database to each Greenplum Database user/role name that will access the HDFS files and directories. If user impersonation is not enabled, you must grant this permission to the
- Time is synchronized between the Greenplum Database segment hosts and the external Hadoop systems.
Examples in the PXF Hadoop topics access files on HDFS. You can choose to access files that already exist in your HDFS cluster. Or, you can follow the steps in the examples to create new files.
A Hadoop installation includes command-line tools that interact directly with your HDFS file system. These tools support typical file system operations that include copying and listing files, changing file permissions, and so forth. You run these tools on a system with a Hadoop client installation. By default, Greenplum Database hosts do not include a Hadoop client installation.
The HDFS file system command syntax is
hdfs dfs <options> [<file>]. Invoked with no options,
hdfs dfs lists the file system options supported by the tool.
The user invoking the
hdfs dfs command must have read privileges on the HDFS data store to list and view directory and file contents, and write permission to create directories and files.
hdfs dfs options used in the PXF Hadoop topics are:
||Display file contents.|
||Create a directory in HDFS.|
||Copy a file from the local file system to HDFS.|
Create a directory in HDFS:
$ hdfs dfs -mkdir -p /data/exampledir
Copy a text file from your local file system to HDFS:
$ hdfs dfs -put /tmp/example.txt /data/exampledir/
Display the contents of a text file located in HDFS:
$ hdfs dfs -cat /data/exampledir/example.txt
The PXF Hadoop connectors provide built-in profiles to support the following data formats:
The PXF Hadoop connectors expose the following profiles to read, and in many cases write, these supported data formats:
|Data Source||Data Format||Profile Name(s)||Deprecated Profile Name|
|HDFS||delimited single line text||hdfs:text||HdfsTextSimple|
|HDFS||delimited text with quoted linefeeds||hdfs:text:multi||HdfsTextMulti|
|Hive||stored as TextFile||Hive, HiveText||n/a|
|Hive||stored as SequenceFile||Hive||n/a|
|Hive||stored as RCFile||Hive, HiveRC||n/a|
|Hive||stored as ORC||Hive, HiveORC, HiveVectorizedORC||n/a|
|Hive||stored as Parquet||Hive||n/a|
PXF provides more than one profile to access text and Parquet data on Hadoop. Here are some things to consider as you determine which profile to choose.
Hive profile when:
- The data resides in a Hive table, and you do not know the underlying file type of the table up front.
- The data resides in a Hive table, and the Hive table is partitioned.
hdfs:text profile when the file is text and you know the location of the file in the HDFS file system.
hdfs:parquet profile when the file is Parquet, you know the location of the file in the HDFS file system, and you want to take advantage of extended filter pushdown support for additional data types and operators.
You must provide the profile name when you specify the
pxf protocol in a
CREATE EXTERNAL TABLE command to create a Greenplum Database external table that references a Hadoop file or directory, HBase table, or Hive table. For example, the following command creates an external table that uses the default server and specifies the profile named
hdfs:text to access the HDFS file
CREATE EXTERNAL TABLE pxf_hdfs_text(location text, month text, num_orders int, total_sales float8) LOCATION ('pxf://data/pxf_examples/pxf_hdfs_simple.txt?PROFILE=hdfs:text') FORMAT 'TEXT' (delimiter=E',');