[
https://issues.apache.org/jira/browse/HAWQ-1107?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15606514#comment-15606514
]
ASF GitHub Bot commented on HAWQ-1107:
--------------------------------------
Github user dyozie commented on a diff in the pull request:
https://github.com/apache/incubator-hawq-docs/pull/33#discussion_r85003214
--- Diff: pxf/HDFSFileDataPXF.html.md.erb ---
@@ -2,388 +2,282 @@
title: Accessing HDFS File Data
---
-## <a id="installingthepxfhdfsplugin"></a>Prerequisites
+HDFS is the primary distributed storage mechanism used by Apache Hadoop
applications. The PXF HDFS plug-in reads file data stored in HDFS. The plug-in
supports plain delimited and comma-separated-value format text files. The HDFS
plug-in also supports the Avro binary format.
-Before working with HDFS file data using HAWQ and PXF, you should perform
the following operations:
+This section describes how to use PXF to access HDFS data, including how
to create and query an external table from files in the HDFS data store.
-- Test PXF on HDFS before connecting to Hive or HBase.
-- Ensure that all HDFS users have read permissions to HDFS services and
that write permissions have been limited to specific users.
+## <a id="hdfsplugin_prereq"></a>Prerequisites
-## <a id="syntax1"></a>Syntax
+Before working with HDFS file data using HAWQ and PXF, ensure that:
-The syntax for creating an external HDFS file is as follows:
+- The HDFS plug-in is installed on all cluster nodes.
+- All HDFS users have read permissions to HDFS services and that write
permissions have been restricted to specific users.
-``` sql
-CREATE [READABLE|WRITABLE] EXTERNAL TABLE table_name
- ( column_name data_type [, ...] | LIKE other_table )
-LOCATION ('pxf://host[:port]/path-to-data?<pxf
parameters>[&custom-option=value...]')
- FORMAT '[TEXT | CSV | CUSTOM]' (<formatting_properties>);
-```
+## <a id="hdfsplugin_fileformats"></a>HDFS File Formats
-where `<pxf parameters>` is:
+The PXF HDFS plug-in supports reading the following file formats:
-``` pre
-
FRAGMENTER=fragmenter_class&ACCESSOR=accessor_class&RESOLVER=resolver_class]
- | PROFILE=profile-name
-```
+- Text File - comma-separated value (.csv) or delimited format plain text
file
+- Avro - JSON-defined, schema-based data serialization format
-**Note:** Omit the `FRAGMENTER` parameter for `READABLE` external tables.
+The PXF HDFS plug-in includes the following profiles to support the file
formats listed above:
-Use an SQL `SELECT` statement to read from an HDFS READABLE table:
+- `HdfsTextSimple` - text files
+- `HdfsTextMulti` - text files with embedded line feeds
+- `Avro` - Avro files
-``` sql
-SELECT ... FROM table_name;
-```
-Use an SQL `INSERT` statement to add data to an HDFS WRITABLE table:
+## <a id="hdfsplugin_cmdline"></a>HDFS Shell Commands
+Hadoop includes command-line tools that interact directly with HDFS.
These tools support typical file system operations including copying and
listing files, changing file permissions, etc.
-``` sql
-INSERT INTO table_name ...;
-```
+The HDFS file system command is `hdfs dfs <options> [<file>]`. Invoked
with no options, `hdfs dfs` lists the file system options supported by the tool.
+
+`hdfs dfs` options used in this section are identified in the table below:
+
+| Option | Description |
+|-------|-------------------------------------|
+| `-cat` | Display file contents. |
+| `-mkdir` | Create directory in HDFS. |
+| `-put` | Copy file from local file system to HDFS. |
+
+### <a id="hdfsplugin_cmdline_create"></a>Create Data Files
+
+Perform the following steps to create data files used in subsequent
exercises:
+
+1. Create an HDFS directory for PXF example data files:
+
+ ``` shell
+ $ sudo -u hdfs hdfs dfs -mkdir -p /data/pxf_examples
+ ```
+
+2. Create a delimited plain text file:
+
+ ``` shell
+ $ vi /tmp/pxf_hdfs_simple.txt
+ ```
+
+3. Copy and paste the following data into `pxf_hdfs_simple.txt`:
+
+ ``` pre
+ Prague,Jan,101,4875.33
+ Rome,Mar,87,1557.39
+ Bangalore,May,317,8936.99
+ Beijing,Jul,411,11600.67
+ ```
+
+ Notice the use of the comma `,` to separate the four data fields.
+
+4. Add the data file to HDFS:
+
+ ``` shell
+ $ sudo -u hdfs hdfs dfs -put /tmp/pxf_hdfs_simple.txt
/data/pxf_examples/
+ ```
+
+5. Display the contents of the `pxf_hdfs_simple.txt` file stored in HDFS:
+
+ ``` shell
+ $ sudo -u hdfs hdfs dfs -cat /data/pxf_examples/pxf_hdfs_simple.txt
+ ```
+
+6. Create a second delimited plain text file:
+
+ ``` shell
+ $ vi /tmp/pxf_hdfs_multi.txt
+ ```
-To read the data in the files or to write based on the existing format,
use `FORMAT`, `PROFILE`, or one of the classes.
-
-This topic describes the following:
-
-- FORMAT clause
-- Profile
-- Accessor
-- Resolver
-- Avro
-
-**Note:** For more details about the API and classes, see [PXF External
Tables and
API](PXFExternalTableandAPIReference.html#pxfexternaltableandapireference).
-
-### <a id="formatclause"></a>FORMAT clause
-
-Use one of the following formats to read data with any PXF connector:
-
-- `FORMAT 'TEXT'`: Use with plain delimited text files on HDFS.
-- `FORMAT 'CSV'`: Use with comma-separated value files on HDFS.
-- `FORMAT 'CUSTOM'`: Use with all other files, including Avro format and
binary formats. Must always be used with the built-in formatter
'`pxfwritable_import`' (for read) or '`pxfwritable_export`' (for write).
-
-**Note:** When creating PXF external tables, you cannot use the `HEADER`
option in your `FORMAT` specification.
-
-### <a id="topic_ab2_sxy_bv"></a>Profile
-
-For plain or comma-separated text files in HDFS use either the
`HdfsTextSimple` or `HdfsTextMulti` Profile, or the classname
org.apache.hawq.pxf.plugins.hdfs.*HdfsDataFragmenter*. Use the `Avro` profile
for Avro files. See [Using Profiles to Read and Write
Data](ReadWritePXF.html#readingandwritingdatawithpxf) for more information.
-
-**Note:** For read tables, you must include a Profile or a Fragmenter in
the table definition.
-
-### <a id="accessor"></a>Accessor
-
-The choice of an Accessor depends on the HDFS data file type.
-
-**Note:** You must include either a Profile or an Accessor in the table
definition.
-
-<table>
-<colgroup>
-<col width="25%" />
-<col width="25%" />
-<col width="25%" />
-<col width="25%" />
-</colgroup>
-<thead>
-<tr class="header">
-<th>File Type</th>
-<th>Accessor</th>
-<th>FORMAT clause</th>
-<th>Comments</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td>Plain Text delimited</td>
-<td>org.apache.hawq.pxf.plugins. hdfs.LineBreakAccessor</td>
-<td>FORMAT 'TEXT' (<em>format param list</em>)</td>
-<td> Read + Write
-<p>You cannot use the <code class="ph codeph">HEADER</code>
option.</p></td>
-</tr>
-<tr class="even">
-<td>Plain Text CSV </td>
-<td>org.apache.hawq.pxf.plugins. hdfs.LineBreakAccessor</td>
-<td>FORMAT 'CSV' (<em>format param list</em>) </td>
-<td><p>LineBreakAccessor is parallel and faster.</p>
-<p>Use if each logical data row is a physical data line.</p>
-<p>Read + Write </p>
-<p>You cannot use the <code class="ph codeph">HEADER</code>
option.</p></td>
-</tr>
-<tr class="odd">
-<td>Plain Text CSV </td>
-<td>org.apache.hawq.pxf.plugins. hdfs.QuotedLineBreakAccessor</td>
-<td>FORMAT 'CSV' (<em>format param list</em>) </td>
-<td><p>QuotedLineBreakAccessor is slower and non-parallel.</p>
-<p>Use if the data includes embedded (quoted) linefeed characters.</p>
-<p>Read Only </p>
-<p>You cannot use the <code class="ph codeph">HEADER</code>
option.</p></td>
-</tr>
-<tr class="even">
-<td>SequenceFile</td>
-<td>org.apache.hawq.pxf.plugins. hdfs.SequenceFileAccessor</td>
-<td>FORMAT 'CUSTOM' (formatter='pxfwritable_import')</td>
-<td> Read + Write (use formatter='pxfwritable_export' for write)</td>
-</tr>
-<tr class="odd">
-<td>AvroFile</td>
-<td>org.apache.hawq.pxf.plugins. hdfs.AvroFileAccessor</td>
-<td>FORMAT 'CUSTOM' (formatter='pxfwritable_import')</td>
-<td> Read Only</td>
-</tr>
-</tbody>
-</table>
-
-### <a id="resolver"></a>Resolver
-
-Choose the Resolver format if data records are serialized in the HDFS
file.
-
-**Note:** You must include a Profile or a Resolver in the table definition.
-
-<table>
-<colgroup>
-<col width="33%" />
-<col width="33%" />
-<col width="33%" />
-</colgroup>
-<thead>
-<tr class="header">
-<th>Record Serialization</th>
-<th>Resolver</th>
-<th>Comments</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td>Avro</td>
-<td>org.apache.hawq.pxf.plugins. hdfs.AvroResolver</td>
-<td><ul>
-<li>Avro files include the record schema, Avro serialization can be used
in other file types (e.g, Sequence File). </li>
-<li>For Avro serialized records outside of an Avro file, include a schema
file name (.avsc) in the url under the optional <code class="ph
codeph">Schema-Data </code>option.</li>
-<li>Deserialize Only (Read) .</li>
-</ul></td>
-</tr>
-<tr class="even">
-<td>Java Writable</td>
-<td>org.apache.hawq.pxf.plugins. hdfs.WritableResolver</td>
-<td><ul>
-<li>Include the name of the Java class that uses Writable serialization in
the URL under the optional <code class="ph codeph">Schema-Data.</code></li>
-<li>The class file must exist in the public stage directory (or in
Hadoop's class path).</li>
-<li>Deserialize and Serialize (Read + Write). </li>
-<li>See <a href="#customizedwritableschemafileguidelines">Customized
Writable Schema File Guidelines</a>.</li>
-</ul></td>
-</tr>
-<tr class="odd">
-<td>None (plain text)</td>
-<td>org.apache.hawq.pxf.plugins. hdfs.StringPassResolver</td>
-<td><ul>
-<li>Does not serialize plain text records. The database parses plain
records. Passes records as they are.</li>
-<li>Deserialize and Serialize (Read + Write).</li>
-</ul></td>
-</tr>
-</tbody>
-</table>
-
-#### <a id="customizedwritableschemafileguidelines"></a>Schema File
Guidelines for WritableResolver
-
-When using a WritableResolver, a schema file needs to be defined. The file
needs to be a Java class file and must be on the class path of PXF.
-
-The class file must follow the following requirements:
-
-1. Must implement org.apache.hadoop.io.Writable interface.
-2. WritableResolver uses reflection to recreate the schema and populate
its fields (for both read and write). Then it uses the Writable interface
functions to read/write. Therefore, fields must be public, to enable access to
them. Private fields will be ignored.
-3. Fields are accessed and populated in the order in which they are
declared in the class file.
-4. Supported field types:
- - boolean
- - byte array
- - double
- - float
- - int
- - long
- - short
- - string
-
- Arrays of any of the above types are supported, but the constructor
must define the array size so the reflection will work.
-
-### <a id="additionaloptions"></a>Additional Options
-
-<a id="additionaloptions__table_skq_kpz_4p"></a>
-
-<table>
-<caption><span class="tablecap">Table 1. Additional PXF
Options</span></caption>
-<colgroup>
-<col width="50%" />
-<col width="50%" />
-</colgroup>
-<thead>
-<tr class="header">
-<th>Option Name</th>
-<th>Description</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td>COLLECTION_DELIM</td>
-<td>(Avro or Hive profiles only.) The delimiter character(s) to place
between entries in a top-level array, map, or record field when PXF maps a Hive
or Avro complex data type to a text column. The default is a ","
character.</td>
-</tr>
-<tr class="even">
-<td>COMPRESSION_CODEC</td>
-<td><ul>
-<li>Useful for WRITABLE PXF tables.</li>
-<li>Specifies the compression codec class name for compressing the written
data. The class must implement the
org.apache.hadoop.io.compress.CompressionCodec interface.</li>
-<li> Some valid values are org.apache.hadoop.io.compress.DefaultCodec
org.apache.hadoop.io.compress.GzipCodec
org.apache.hadoop.io.compress.BZip2Codec.</li>
-<li>Note: org.apache.hadoop.io.compress.BZip2Codec runs in a single thread
and can be slow.</li>
-<li>This option has no default value. </li>
-<li>When the option is not defined, no compression will be done.</li>
-</ul></td>
-</tr>
-<tr class="odd">
-<td>COMPRESSION_TYPE</td>
-<td><ul>
-<li>Useful WRITABLE PXF tables with SequenceFileAccessor.</li>
-<li>Ignored when COMPRESSION_CODEC is not defined.</li>
-<li>Specifies the compression type for sequence file.</li>
-<li>Valid options are:
-<ul>
-<li>RECORD - only the value part of each row is compressed.</li>
-<li>BLOCK - both keys and values are collected in 'blocks' separately and
compressed.</li>
-</ul></li>
-<li>Default value: RECORD.</li>
-</ul></td>
-</tr>
-<tr class="even">
-<td>MAPKEY_DELIM</td>
-<td>(Avro or Hive profiles only.) The delimiter character(s) to place
between the key and value of a map entry when PXF maps a Hive or Avro complex
data type to a text colum. The default is a ":" character.</td>
-</tr>
-<tr class="odd">
-<td>RECORDKEY_DELIM</td>
-<td>(Avro profile only.) The delimiter character(s) to place between the
field name and value of a record entry when PXF maps an Avro complex data type
to a text colum. The default is a ":" character.</td>
-</tr>
-<tr class="even">
-<td>SCHEMA-DATA</td>
-<td>The data schema file used to create and read the HDFS file. For
example, you could create an avsc (for Avro), or a Java class (for Writable
Serialization) file. Make sure that you have added any JAR files containing the
schema to <code class="ph codeph">pxf-public.classpath</code>.
-<p>This option has no default value.</p></td>
-</tr>
-<tr class="odd">
-<td>THREAD-SAFE</td>
-<td>Determines if the table query can run in multithread mode or not. When
set to FALSE, requests will be handled in a single thread.
-<p>Should be set when a plug-in or other elements that are not thread safe
are used (e.g. compression codec).</p>
-<p>Allowed values: TRUE, FALSE. Default value is TRUE - requests can run
in multithread mode.</p></td>
-</tr>
-<tr class="even">
-<td> <custom></td>
-<td>Any option added to the pxf URI string will be accepted and passed,
along with its value, to the Fragmenter, Accessor, and Resolver
implementations.</td>
-</tr>
-</tbody>
-</table>
-
-## <a id="accessingdataonahighavailabilityhdfscluster"></a>Accessing Data
on a High Availability HDFS Cluster
-
-To access data on a High Availability HDFS cluster, change the authority
in the URI in the LOCATION. Use *HA\_nameservice* instead of
*name\_node\_host:51200*.
+7. Copy/paste the following data into `pxf_hdfs_multi.txt`:
+
+ ``` pre
+ "4627 Star Rd.
+ San Francisco, CA 94107":Sept:2017
+ "113 Moon St.
+ San Diego, CA 92093":Jan:2018
+ "51 Belt Ct.
+ Denver, CO 90123":Dec:2016
+ "93114 Radial Rd.
+ Chicago, IL 60605":Jul:2017
+ "7301 Brookview Ave.
+ Columbus, OH 43213":Dec:2018
+ ```
+
+ Notice the use of the colon `:` to separate the three fields. Also
notice the quotes around the first (address) field. This field includes an
embedded line feed.
+
+8. Add the data file to HDFS:
+
+ ``` shell
+ $ sudo -u hdfs hdfs dfs -put /tmp/pxf_hdfs_multi.txt
/data/pxf_examples/
+ ```
+
+You will use these HDFS files in later sections.
+
+## <a id="hdfsplugin_queryextdata"></a>Querying External HDFS Data
+The PXF HDFS plug-in supports the `HdfsTextSimple`, `HdfsTextMulti`, and
`Avro` profiles.
+
+Use the following syntax to create a HAWQ external table representing HDFS
data:
``` sql
-CREATE [READABLE|WRITABLE] EXTERNAL TABLE <tbl name> (<attr list>)
-LOCATION ('pxf://<HA nameservice>/<path to file or
directory>?Profile=profile[&<additional options>=<value>]')
-FORMAT '[TEXT | CSV | CUSTOM]' (<formatting properties>);
+CREATE EXTERNAL TABLE <table_name>
+ ( <column_name> <data_type> [, ...] | LIKE <other_table> )
+LOCATION ('pxf://<host>[:<port>]/<path-to-hdfs-file>
+
?PROFILE=HdfsTextSimple|HdfsTextMulti|Avro[&<custom-option>=<value>[...]]')
+FORMAT '[TEXT|CSV|CUSTOM]' (<formatting-properties>);
```
-The opposite is true when a highly available HDFS cluster is reverted to a
single namenode configuration. In that case, any table definition that has the
nameservice specified should use the <NN host>:<NN rest port>
syntax.
+HDFS-plug-in-specific keywords and values used in the [CREATE EXTERNAL
TABLE](../reference/sql/CREATE-EXTERNAL-TABLE.html) call are described in the
table below.
+
+| Keyword | Value |
+|-------|-------------------------------------|
+| \<host\>[:\<port\>] | The HDFS NameNode and port. |
+| \<path-to-hdfs-file\> | The path to the file in the HDFS data store. |
+| PROFILE | The `PROFILE` keyword must specify one of the values
`HdfsTextSimple`, `HdfsTextMulti`, or `Avro`. |
+| \<custom-option\> | \<custom-option\> is profile-specific.
Profile-specific options are discussed in the relevant profile topic later in
this section.|
+| FORMAT 'TEXT' | Use '`TEXT`' `FORMAT` with the `HdfsTextSimple` profile
when \<path-to-hdfs-file\> references a plain text delimited file. |
+| FORMAT 'CSV' | Use '`CSV`' `FORMAT` with `HdfsTextSimple` and
`HdfsTextMulti` profiles when \<path-to-hdfs-file\> references a
comma-separated value file. |
+| FORMAT 'CUSTOM' | Use the`CUSTOM` `FORMAT` with the `Avro` profile. The
`Avro` '`CUSTOM`' `FORMAT` supports only the built-in
`(formatter='pxfwritable_import')` \<formatting-property\> |
+ \<formatting-properties\> | \<formatting-properties\> are
profile-specific. Profile-specific formatting options are discussed in the
relevant profile topic later in this section. |
+
+*Note*: When creating PXF external tables, you cannot use the `HEADER`
option in your `FORMAT` specification.
-## <a id="recordkeyinkey-valuefileformats"></a>Using a Record Key with
Key-Value File Formats
+## <a id="profile_hdfstextsimple"></a>HdfsTextSimple Profile
-For sequence file and other file formats that store rows in a key-value
format, the key value can be accessed through HAWQ by using the saved keyword
'`recordkey`' as a field name.
+Use the `HdfsTextSimple` profile when reading plain text delimited or .csv
files where each row is a single record.
-The field type must correspond to the key type, much as the other fields
must match the HDFS data.
+\<formatting-properties\> supported by the `HdfsTextSimple` profile
include:
-WritableResolver supports read and write of recordkey, which can be of the
following Writable Hadoop types:
+| Keyword | Value |
+|-------|-------------------------------------|
+| delimiter | The delimiter character in the file. Default value is a
comma `,`.|
-- BooleanWritable
-- ByteWritable
-- DoubleWritable
-- FloatWritable
-- IntWritable
-- LongWritable
-- Text
-If the `recordkey` field is not defined, the key is ignored in read, and a
default value (segment id as LongWritable) is written in write.
+The following SQL call uses the PXF `HdfsTextSimple` profile to create a
queryable HAWQ external table from the `pxf_hdfs_simple.txt` file you created
and added to HDFS in an earlier section:
+
+``` sql
+gpadmin=# CREATE EXTERNAL TABLE pxf_hdfs_textsimple(location text, month
text, num_orders int, total_sales float8)
+ LOCATION
('pxf://namenode:51200/data/pxf_examples/pxf_hdfs_simple.txt?PROFILE=HdfsTextSimple')
+ FORMAT 'TEXT' (delimiter=E',');
+gpadmin=# SELECT * FROM pxf_hdfs_textsimple;
+```
-### <a id="example1"></a>Example
+``` pre
+ location | month | num_orders | total_sales
+---------------+-------+------------+-------------
+ Prague | Jan | 101 | 4875.33
+ Rome | Mar | 87 | 1557.39
+ Bangalore | May | 317 | 8936.99
+ Beijing | Jul | 411 | 11600.67
+(4 rows)
+```
-A data schema `Babies.class` contains three fields: (name text, birthday
text, weight float). An external table must include these three fields, and can
either include or ignore the recordkey.
+Create a second external table from `pxf_hdfs_simple.txt`, this time using
the `CSV` `FORMAT`:
``` sql
--- writable table with recordkey
-CREATE WRITABLE EXTERNAL TABLE babies_registry (recordkey int, name text,
birthday text, weight float)
- LOCATION ('pxf://namenode_host:51200/babies_1940s'
-
'?ACCESSOR=org.apache.hawq.pxf.plugins.hdfs.SequenceFileAccessor'
- '&RESOLVER=org.apache.hawq.pxf.plugins.hdfs.WritableResolver'
- '&DATA-SCHEMA=Babies')
- FORMAT 'CUSTOM' (formatter='pxfwritable_export');
-INSERT INTO babies_registry VALUES (123456, "James Paul McCartney", "June
18, 1942", 3.800);
-
--- writable table without recordkey
-CREATE WRITABLE EXTERNAL TABLE babies_registry2 (name text, birthday text,
weight float)
- LOCATION ('pxf://namenode_host:51200/babies_1940s'
- '?ACCESSOR=org.apache.hawq.pxf.plugins.SequenceFileAccessor'
- '&RESOLVER=org.apache.hawq.pxf.plugins.WritableResolver'
- '&DATA-SCHEMA=Babies')
- FORMAT 'CUSTOM' (formatter='pxfwritable_export');
-
--- this record's key will have some default value
-INSERT INTO babies_registry VALUES ("Richard Starkey", "July 7, 1940",
4.0);
+gpadmin=# CREATE EXTERNAL TABLE pxf_hdfs_textsimple_csv(location text,
month text, num_orders int, total_sales float8)
+ LOCATION
('pxf://namenode:51200/data/pxf_examples/pxf_hdfs_simple.txt?PROFILE=HdfsTextSimple')
+ FORMAT 'CSV';
+gpadmin=# SELECT * FROM pxf_hdfs_textsimple_csv;
```
-The same goes for reading data from an existing file with a key-value
format, e.g. a Sequence file.
+Notice: When specifying `FORMAT 'CSV'` for a comma-separated value file,
no `delimiter` formatter option is required, as comma is the default.
+
+## <a id="profile_hdfstextmulti"></a>HdfsTextMulti Profile
+
+Use the `HdfsTextMulti` profile when reading plain text files with
delimited single- or multi- line records that include embedded (quoted)
linefeed characters.
+
+\<formatting-properties\> supported by the `HdfsTextMulti` profile include:
+
+| Keyword | Value |
+|-------|-------------------------------------|
+| delimiter | The delimiter character in the file. |
+
+The following SQL call uses the PXF `HdfsTextMulti` profile to create a
queryable HAWQ external table from the `pxf_hdfs_multi.txt` file you created
and added to HDFS in an earlier section:
``` sql
--- readable table with recordkey
-CREATE EXTERNAL TABLE babies_1940 (recordkey int, name text, birthday
text, weight float)
- LOCATION ('pxf://namenode_host:51200/babies_1940s'
-
'?FRAGMENTER=org.apache.hawq.pxf.plugins.hdfs.HdfsDataFragmenter'
-
'&ACCESSOR=org.apache.hawq.pxf.plugins.hdfs.SequenceFileAccessor'
- '&RESOLVER=org.apache.hawq.pxf.plugins.hdfs.WritableResolver'
- '&DATA-SCHEMA=Babies')
- FORMAT 'CUSTOM' (formatter='pxfwritable_import');
--- retrieve each record's key
-SELECT * FROM babies_1940;
-
--- readable table without recordkey
-CREATE EXTERNAL TABLE babies_1940_2 (name text, birthday text, weight
float)
- LOCATION ('pxf://namenode_host:51200/babies_1940s'
-
'?FRAGMENTER=org.apache.hawq.pxf.plugins.hdfs.HdfsDataFragmenter'
-
'&ACCESSOR=org.apache.hawq.pxf.plugins.hdfs.SequenceFileAccessor'
- '&RESOLVER=org.apache.hawq.pxf.plugins.hdfs.WritableResolver'
- '&DATA-SCHEMA=Babies')
- FORMAT 'CUSTOM' (formatter='pxfwritable_import');
--- ignores the records' key
-SELECT * FROM babies_1940_2;
+gpadmin=# CREATE EXTERNAL TABLE pxf_hdfs_textmulti(address text, month
text, year int)
+ LOCATION
('pxf://namenode:51200/data/pxf_examples/pxf_hdfs_multi.txt?PROFILE=HdfsTextMulti')
+ FORMAT 'CSV' (delimiter=E':');
+gpadmin=# SELECT * FROM pxf_hdfs_textmulti;
+```
+
+``` pre
+ address | month | year
+--------------------------+-------+------
+ 4627 Star Rd. | Sept | 2017
+ San Francisco, CA 94107
+ 113 Moon St. | Jan | 2018
+ San Diego, CA 92093
+ 51 Belt Ct. | Dec | 2016
+ Denver, CO 90123
+ 93114 Radial Rd. | Jul | 2017
+ Chicago, IL 60605
+ 7301 Brookview Ave. | Dec | 2018
+ Columbus, OH 43213
+(5 rows)
```
-## <a id="topic_oy3_qwm_ss"></a>Working with Avro Files
+## <a id="profile_hdfsavro"></a>Avro Profile
+
+Apache Avro is a data serialization framework where the data is serialized
in a compact binary format.
+
+Avro specifies data types be defined in JSON. Avro format files have an
independent schema, also defined in JSON. In Avro files, the schema is stored
with the data. An Avro schema, together with its data, is fully self-describing.
-Avro files combine their data with a schema, and can support complex data
types such as arrays, maps, records, enumerations, and fixed types. When you
create a PXF external table to represent Avro data, map top-level fields in the
schema that use a primitive data type to HAWQ columns of the same type. Map
top-level fields that use a complex data type to a TEXT column in the external
table. The PXF Avro profile automatically separates components of a complex
type by inserting delimiters in the text column. You can then use functions or
application code to further process components of the complex data.
+### <a id="profile_hdfsavrodatamap"></a>Data Type Mapping
-The following table summarizes external table mapping rules for Avro data.
+Avro supports both primitive and complex data types.
-<caption><span class="tablecap">Table 2. Avro Data Type
Mapping</span></caption>
+To represent Avro primitive data types in HAWQ, map data values to HAWQ
columns of the same type.
+
+Avro supports complex data types including arrays, maps, records,
enumerations, and fixed types. Map top-level fields of these complex data types
to the HAWQ `TEXT` type. While HAWQ does not natively support these types, you
can create HAWQ functions or application code to extract or further process
subcomponents of these complex data types.
+
+The following table summarizes external mapping rules for Avro data.
<a id="topic_oy3_qwm_ss__table_j4s_h1n_ss"></a>
-| Avro Data Type | PXF
Type
|
+| Avro Data Type |
PXF/HAWQ Data Type
|
|-------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| Primitive type (int, double, float, long, string, bytes, boolean) |
Corresponding HAWQ data type. See [Data
Types](../reference/HAWQDataTypes.html). |
-| Complex type: Array, Map, Record, or Enum |
TEXT, with default delimiters inserted between collection items, mapped
key-value pairs, and record data.
|
+| Primitive type (int, double, float, long, string, bytes, boolean) | Use
the corresponding HAWQ built-in data type; see [Data
Types](../reference/HAWQDataTypes.html). |
+| Complex type: Array, Map, Record, or Enum |
TEXT, with delimiters inserted between collection items, mapped key-value
pairs, and record data.
|
| Complex type: Fixed |
BYTEA
|
-| Union |
Follows the above conventions for primitive or complex data types, depending on
the union. Null values are supported in Unions.
|
+| Union |
Follows the above conventions for primitive or complex data types, depending on
the union; supports Null values.
|
+
+### <a id="profile_hdfsavroptipns"></a>Avro-Specific Custom Options
+
+For complex types, the PXF `Avro` profile inserts default delimiters
between collection items and values. You can use non-default delimiter
characters by identifying values for specific `Avro` custom options in the
`CREATE EXTERNAL TABLE` call.
+
+The `Avro` profile supports the following \<custom-options\>:
+
+| Option Name | Description
+|---------------|--------------------|
+| COLLECTION_DELIM | The delimiter character(s) to place between entries
in a top-level array, map, or record field when PXF maps an Avro complex data
type to a text column. The default is a comma `,` character. |
+| MAPKEY_DELIM | The delimiter character(s) to place between the key and
value of a map entry when PXF maps an Avro complex data type to a text column.
The default is a colon `:` character. |
+| RECORDKEY_DELIM | The delimiter character(s) to place between the field
name and value of a record entry when PXF maps an Avro complex data type to a
text column. The default is a colon `:` character. |
+
-For complex types, the PXF Avro profile inserts default delimiters between
collection items and values. You can use non-default delimiter characters by
including the `COLLECTION_DELIM`, `MAPKEY_DELIM`, and/or `RECORDKEY_DELIM`
optional parameters on the Avro profile. See [Additional PXF
Options](#additionaloptions__table_skq_kpz_4p) for a description of the
parameters.
+### <a id="topic_tr3_dpg_ts__section_m2p_ztg_ts"></a>Avro Schemas
-### <a id="topic_tr3_dpg_ts"></a>Example
+Avro schemas are defined using JSON, and composed of the same primitive
and complex types identified in the data mapping section above. Avro schema
files typically have a `.avsc` suffix.
--- End diff --
The earlier section said an Avro schema is stored along with its data,
rather than in a separate file...
> PXF HDFS documentation - restructure content and include more examples
> ----------------------------------------------------------------------
>
> Key: HAWQ-1107
> URL: https://issues.apache.org/jira/browse/HAWQ-1107
> Project: Apache HAWQ
> Issue Type: Improvement
> Components: Documentation
> Reporter: Lisa Owen
> Assignee: David Yozie
> Priority: Minor
> Fix For: 2.0.1.0-incubating
>
>
> the current PXF HDFS documentation does not include any runnable examples.
> add runnable examples for all (HdfsTextSimple, HdfsTextMulti, SerialWritable,
> Avro) profiles. restructure the content as well.
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