PXF is compatible with Cloudera, Hortonworks Data Platform, 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 coordinator host dispatches the query to all segment instances. Each segment instance contacts the PXF Service running on its host. When it receives the request from a segment instance, the PXF Service:
Figure: PXF-to-Hadoop Architecture
A PXF worker thread works on behalf of a segment instance. A worker thread 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. This data may reside on one or more HDFS DataNodes.
The PXF worker thread 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 coordinator host. This communication occurs across segment hosts and segment instances in parallel.
Before working with Hadoop data using PXF, ensure that:
gpadmin
user.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.
The hdfs dfs
options used in the PXF Hadoop topics are:
Option | Description |
---|---|
-cat |
Display file contents. |
-mkdir |
Create a directory in HDFS. |
-put |
Copy a file from the local file system to HDFS. |
Examples:
Create a directory in HDFS:
$ hdfs dfs -mkdir -p /data/pxf_examples
Copy a text file from your local file system to HDFS:
$ hdfs dfs -put /tmp/example.txt /data/pxf_examples/
Display the contents of a text file located in HDFS:
$ hdfs dfs -cat /data/pxf_examples/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 | Supported Operations |
---|---|---|---|---|
HDFS | delimited single line text | hdfs:text | n/a | Read, Write |
HDFS | delimited single line comma-separated values of text | hdfs:csv | n/a | Read, Write |
HDFS | multi-byte or multi-character delimited single line csv | hdfs:csv | n/a | Read |
HDFS | fixed width single line text | hdfs:fixedwidth | n/a | Read, Write |
HDFS | delimited text with quoted linefeeds | hdfs:text:multi | n/a | Read |
HDFS | Avro | hdfs:avro | n/a | Read, Write |
HDFS | JSON | hdfs:json | n/a | Read, Write |
HDFS | ORC | hdfs:orc | n/a | Read, Write |
HDFS | Parquet | hdfs:parquet | n/a | Read, Write |
HDFS | AvroSequenceFile | hdfs:AvroSequenceFile | n/a | Read, Write |
HDFS | SequenceFile | hdfs:SequenceFile | n/a | Read, Write |
Hive | stored as TextFile | hive, [hive:text] (hive_pxf.html#hive_text) | Hive, HiveText | Read |
Hive | stored as SequenceFile | hive | Hive | Read |
Hive | stored as RCFile | hive, hive:rc | Hive, HiveRC | Read |
Hive | stored as ORC | hive, hive:orc | Hive, HiveORC, HiveVectorizedORC | Read |
Hive | stored as Parquet | hive | Hive | Read |
Hive | stored as Avro | hive | Hive | Read |
HBase | Any | hbase | HBase | Read |
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.
Choose the hive
profile when:
Choose the hdfs:text
, hdfs:csv
profiles when the file is text and you know the location of the file in the HDFS file system.
When accessing ORC-format data:
hdfs:orc
profile when the file is ORC, you know the location of the file in the HDFS file system, and the file is not managed by Hive or you do not want to use the Hive Metastore.hive:orc
profile when the table is ORC and the table is managed by Hive, and the data is partitioned or the data includes complex types.Choose the 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 /data/pxf_examples/pxf_hdfs_simple.txt
:
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',');