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YARN-5980. Update documentation for single node hbase deploy. Contributed by Vrushali C. 

(cherry picked from commit e1bdba77888723b435a235a96c8659029afd25d5)
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Sangjin Lee 2017-01-13 09:12:48 -08:00 committed by Varun Saxena
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hadoop-yarn-project/hadoop-yarn/hadoop-yarn-site/src/site/markdown/TimelineServiceV2.md
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@ -165,18 +165,64 @@ New configuration parameters that are introduced with v.2 are marked bold.
### <a name="Enabling_Timeline_Service_v2"></a>Enabling Timeline Service v.2
#### Preparing Apache HBase cluster for storage
There are a few steps to be done for preparing the storage for Timeline Service v.2:
Step 1) [Set up the HBase cluster](#Set_up_the_HBase_cluster)
Step 2) [Enable the coprocessor](#Enable_the_coprocessor)
Step 3) [Create the schema for Timeline Service v.2](#Create_schema)
Each step is explained in more detail below.
##### <a name="Set_up_the_HBase_cluster"> </a>Step 1) Set up the HBase cluster
The first part is to set up or pick an Apache HBase cluster to use as the storage cluster. The
version of Apache HBase that is supported with Timeline Service v.2 is 1.1.x. The 1.0.x versions
do not work with Timeline Service v.2. The 1.2.x versions have not been tested.
version of Apache HBase that is supported with Timeline Service v.2 is 1.2.4. The 1.0.x versions
do not work with Timeline Service v.2. Later versions of HBase have not been tested with
Timeline Service.
Once you have an Apache HBase cluster ready to use for this purpose, perform the following steps.
HBase has different deployment modes. Refer to the HBase book for understanding them and pick a
mode that is suitable for your setup.
(http://hbase.apache.org/book.html#standalone_dist)
First, add the timeline service jar to the HBase classpath in all HBase machines in the cluster. It
##### Simple deployment for HBase
If you are intent on a simple deploy profile for the Apache HBase cluster
where the data loading is light but the data needs to persist across node
comings and goings, you could consider the "Standalone HBase over HDFS" deploy mode.
This is a useful variation on the standalone HBase setup and has all HBase daemons running inside
one JVM but rather than persisting to the local filesystem, it persists to an HDFS instance.
Writing to HDFS where data is replicated ensures that data is persisted across node
comings and goings. To configure this standalone variant, edit your `hbase-site.xml` setting
the `hbase.rootdir` to point at a directory in your HDFS instance but then set
`hbase.cluster.distributed` to false. For example:
```
<configuration>
<property>
<name>hbase.rootdir</name>
<value>hdfs://namenode.example.org:8020/hbase</value>
</property>
<property>
<name>hbase.cluster.distributed</name>
<value>false</value>
</property>
</configuration>
```
For more details on this mode, refer to
http://hbase.apache.org/book.html#standalone.over.hdfs .
Once you have an Apache HBase cluster ready to use, perform the following steps.
##### <a name="Enable_the_coprocessor"> </a>Step 2) Enable the coprocessor
Step 2.1) Add the timeline service jar to the HBase classpath in all HBase machines in the cluster. It
is needed for the coprocessor as well as the schema creator. For example,
cp hadoop-yarn-server-timelineservice-3.0.0-alpha1-SNAPSHOT.jar /usr/hbase/lib/
Then, enable the coprocessor that handles the aggregation. To enable it, add the following entry in
Step 2.2) Enable the coprocessor that handles the aggregation. To enable it, add the following entry in
region servers' `hbase-site.xml` file (generally located in the `conf` directory) as follows:
```
@ -186,10 +232,11 @@ region servers' `hbase-site.xml` file (generally located in the `conf` directory
</property>
```
Restart the region servers and the master to pick up the timeline service jar as well as the config
change. In this version, the coprocessor is loaded statically (i.e. system coprocessor) as opposed
to a dynamically (table coprocessor).
Step 2.3) Restart the region servers and the master to pick up the timeline service jar as well
as the config change. In this version, the coprocessor is loaded statically
(i.e. system coprocessor) as opposed to a dynamically (table coprocessor).
##### <a name="Create_schema"> </a>Step 3) Create the timeline service schema
Finally, run the schema creator tool to create the necessary tables:
bin/hbase org.apache.hadoop.yarn.server.timelineservice.storage.TimelineSchemaCreator