Github user dyozie commented on a diff in the pull request:
https://github.com/apache/incubator-hawq-docs/pull/39#discussion_r85372086
--- Diff: pxf/HivePXF.html.md.erb ---
@@ -2,121 +2,450 @@
title: Accessing Hive Data
---
-This topic describes how to access Hive data using PXF. You have several
options for querying data stored in Hive. You can create external tables in PXF
and then query those tables, or you can easily query Hive tables by using HAWQ
and PXF's integration with HCatalog. HAWQ accesses Hive table metadata stored
in HCatalog.
+Apache Hive is a distributed data warehousing infrastructure. Hive
facilitates managing large data sets supporting multiple data formats,
including comma-separated value (.csv), RC, ORC, and parquet. The PXF Hive
plug-in reads data stored in Hive, as well as HDFS or HBase.
+
+This section describes how to use PXF to access Hive data. Options for
querying data stored in Hive include:
+
+- Creating an external table in PXF and querying that table
+- Querying Hive tables via PXF's integration with HCatalog
## <a id="installingthepxfhiveplugin"></a>Prerequisites
-Check the following before using PXF to access Hive:
+Before accessing Hive data with HAWQ and PXF, ensure that:
-- The PXF HDFS plug-in is installed on all cluster nodes.
+- The PXF HDFS plug-in is installed on all cluster nodes. See
[Installing PXF Plug-ins](InstallPXFPlugins.html) for PXF plug-in installation
information.
- The PXF Hive plug-in is installed on all cluster nodes.
- The Hive JAR files and conf directory are installed on all cluster
nodes.
-- Test PXF on HDFS before connecting to Hive or HBase.
+- You have tested PXF on HDFS.
- You are running the Hive Metastore service on a machine in your
cluster.Â
- You have set the `hive.metastore.uris`Â property in theÂ
`hive-site.xml` on the NameNode.
+## <a id="topic_p2s_lvl_25"></a>Hive File Formats
+
+Hive supports several file formats:
+
+- TextFile - flat file with data in comma-, tab-, or space-separated
value format or JSON notation
+- SequenceFile - flat file consisting of binary key/value pairs
+- RCFile - record columnar data consisting of binary key/value pairs;
high row compression rate
+- ORCFile - optimized row columnar data with stripe, footer, and
postscript sections; reduces data size
+- Parquet - compressed columnar data representation
+- Avro - JSON-defined, schema-based data serialization format
+
+Refer to [File
Formats](https://cwiki.apache.org/confluence/display/Hive/FileFormats) for
detailed information about the file formats supported by Hive.
+
+The PXF Hive plug-in supports the following profiles for accessing the
Hive file formats listed above. These include:
+
+- `Hive`
+- `HiveText`
+- `HiveRC`
+
+## <a id="topic_p2s_lvl_29"></a>Data Type Mapping
+
+### <a id="hive_primdatatypes"></a>Primitive Data Types
+
+To represent Hive data in HAWQ, map data values that use a primitive data
type to HAWQ columns of the same type.
+
+The following table summarizes external mapping rules for Hive primitive
types.
+
+| Hive Data Type | Hawq Data Type |
+|-------|---------------------------|
+| boolean | bool |
+| int | int4 |
+| smallint | int2 |
+| tinyint | int2 |
+| bigint | int8 |
+| decimal | numeric |
+| float | float4 |
+| double | float8 |
+| string | text |
+| binary | bytea |
+| char | bpchar |
+| varchar | varchar |
+| timestamp | timestamp |
+| date | date |
+
+
+### <a id="topic_b4v_g3n_25"></a>Complex Data Types
+
+Hive supports complex data types including array, struct, map, and union.
PXF maps each of these complex types to `text`. While HAWQ does not natively
support these types, you can create HAWQ functions or application code to
extract subcomponents of these complex data types.
+
+An example using complex data types is provided later in this topic.
+
+
+## <a id="hive_sampledataset"></a>Sample Data Set
+
+Examples used in this topic will operate on a common data set. This simple
data set models a retail sales operation and includes fields with the following
names and data types:
+
+- location - text
+- month - text
+- number\_of\_orders - integer
+- total\_sales - double
+
+Prepare the sample data set for use:
+
+1. First, create a text file:
+
+ ```
+ $ vi /tmp/pxf_hive_datafile.txt
+ ```
+
+2. Add the following data to `pxf_hive_datafile.txt`; notice the use of
the comma `,` to separate the four field values:
+
+ ```
+ Prague,Jan,101,4875.33
+ Rome,Mar,87,1557.39
+ Bangalore,May,317,8936.99
+ Beijing,Jul,411,11600.67
+ San Francisco,Sept,156,6846.34
+ Paris,Nov,159,7134.56
+ San Francisco,Jan,113,5397.89
+ Prague,Dec,333,9894.77
+ Bangalore,Jul,271,8320.55
+ Beijing,Dec,100,4248.41
+ ```
+
+Make note of the path to `pxf_hive_datafile.txt`; you will use it in later
exercises.
+
+
## <a id="hivecommandline"></a>Hive Command Line
-To start the Hive command line and work directly on a Hive table:
+The Hive command line is a subsystem similar to that of `psql`. To start
the Hive command line:
``` shell
-$ hive
+$ HADOOP_USER_NAME=hdfs hive
```
-Here is an example of how to create and load data into a sample Hive
table from an existing file.
+The default Hive database is named `default`.
-``` sql
-hive> CREATE TABLE test (name string, type string, supplier_key int,
full_price double) row format delimited fields terminated by ',';
-hive> LOAD DATA local inpath '/local/path/data.txt' into table test;
-```
+### <a id="hivecommandline_createdb"></a>Example: Create a Hive Database
-## <a id="topic_p2s_lvl_25"></a>Using PXF Tables to Query Hive
+Create a Hive table to expose our sample data set.
-Hive tables are defined in a specific way in PXF, regardless of the
underlying file storage format. The PXF Hive plug-ins automatically detect
source tables in the following formats:
+1. Create a Hive table named `sales_info` in the `default` database:
-- Text based
-- SequenceFile
-- RCFile
-- ORCFile
-- Parquet
-- Avro
+ ``` sql
+ hive> CREATE TABLE sales_info (location string, month string,
+ number_of_orders int, total_sales double)
+ ROW FORMAT DELIMITED FIELDS TERMINATED BY ','
+ STORED AS textfile;
+ ```
-The source table can also be a combination of these types. The PXF Hive
plug-in uses this information to query the data in runtime.
+ Notice that:
-- **[Syntax Example](../pxf/HivePXF.html#syntax2)**
+ - The `STORED AS textfile` subclause instructs Hive to create the
table in Textfile (the default) format. Hive Textfile format supports comma-,
tab-, and space-separated values, as well as data specified in JSON notation.
+ - The `DELIMITED FIELDS TERMINATED BY` subclause identifies the field
delimiter within a data record (line). The `sales_info` table field delimiter
is a comma (`,`).
-- **[Hive Complex Types](../pxf/HivePXF.html#topic_b4v_g3n_25)**
+2. Load the `pxf_hive_datafile.txt` sample data file into the `sales_info`
table you just created:
-### <a id="syntax2"></a>Syntax Example
+ ``` sql
+ hive> LOAD DATA local INPATH '/tmp/pxf_hive_datafile.txt'
+ INTO TABLE sales_info;
+ ```
+
+3. Perform a query on `sales_info` to verify the data was loaded
successfully:
--- End diff --
Global edit to change "verify the data" -> "verify that the data"
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