@InterfaceStability.Unstable @InterfaceAudience.Public public class PreWarmVertex extends Vertex
PreWarmVertex is used to specify parameters to be used to setup
 prewarmed containers for Tez session mode. Sessions allow re-use of execution
 slots (containers) across DAG's. Pre- warming allows pre-allocation of
 containers so that the first DAG has some execution resources already
 available to re-use. In order to get re-use containers they must be setup
 identically. So the prewarm vertex must be setup identically to the real DAG
 vertex (typically the first vertex to execute in the read DAG). Identical
 settings include same execution resources, same task local files etc. This
 works best in use cases where all DAGs share the same files/jars/resource
 settings from a common templateTezConfiguration.TEZ_AM_SESSION_MIN_HELD_CONTAINERS property. The
 prewarm vertex by default runs the PreWarmProcessor from the Tez runtime
 library. This processor can be overridden to get the default behavior along
 with any app specific customizations. Alternatively, the application can
 provide any Processor to prewarm the containers. Pre-warming
 processors can be used to initialize classes etc. and setup the environment
 for the actual processing to reduce latency.| Modifier and Type | Method and Description | 
|---|---|
| static PreWarmVertex | create(String vertexName,
      int parallelism,
      org.apache.hadoop.yarn.api.records.Resource taskResource)Create a  PreWarmVertexto be used in @linkTezClient.preWarm(PreWarmVertex)This uses a built in pre-warm
 processor that implements common functionality. | 
| static PreWarmVertex | create(String vertexName,
      ProcessorDescriptor processorDescriptor,
      int parallelism,
      org.apache.hadoop.yarn.api.records.Resource taskResource)Create a  PreWarmVertexto be used inTezClient.preWarm(PreWarmVertex)It may be necessary to call more
 methods to add local files etc on the pre-warm vertex post creation so that
 it matches the real DAG vertices. | 
| static org.apache.tez.dag.api.PreWarmVertex.PreWarmVertexConfigBuilder | createConfigBuilder(org.apache.hadoop.conf.Configuration conf)Create a config builder for the @link  PreWarmVertex. | 
addDataSink, addDataSource, addTaskLocalFiles, create, create, equals, getConf, getInputVertices, getName, getOutputVertices, getParallelism, getProcessorDescriptor, getTaskEnvironment, getTaskLaunchCmdOpts, getTaskLocalFiles, getTaskResource, hashCode, setConf, setLocationHint, setTaskEnvironment, setTaskLaunchCmdOpts, setVertexManagerPlugin, toStringpublic static org.apache.tez.dag.api.PreWarmVertex.PreWarmVertexConfigBuilder createConfigBuilder(org.apache.hadoop.conf.Configuration conf)
PreWarmVertex. This may be used to construct the
 pre-warm vertex more flexibly.conf - PreWarmVertexpublic static PreWarmVertex create(String vertexName, ProcessorDescriptor processorDescriptor, int parallelism, org.apache.hadoop.yarn.api.records.Resource taskResource)
PreWarmVertex to be used in
 TezClient.preWarm(PreWarmVertex) It may be necessary to call more
 methods to add local files etc on the pre-warm vertex post creation so that
 it matches the real DAG vertices.vertexName - Name of the vertexprocessorDescriptor - Descriptor of the processor to be runparallelism - Number of containers to be pre-warmedtaskResource - Execution cpu/memory resources etc neededpublic static PreWarmVertex create(String vertexName, int parallelism, org.apache.hadoop.yarn.api.records.Resource taskResource)
PreWarmVertex to be used in @link
 TezClient.preWarm(PreWarmVertex) This uses a built in pre-warm
 processor that implements common functionality. Users may derive from this
 processor to add custom functionality but then they must add the jar for
 that class to the prewarm vertex and other vertices in their DAG for which
 they want the containers to be reused. It may be necessary to call more
 methods to add local files etc on the pre-warm vertex post creation so that
 it matches the real DAG vertices.vertexName - Name of the vertexparallelism - Number of containers to be pre-warmedtaskResource - Execution cpu/memory resources etc neededCopyright © 2016 Apache Software Foundation. All rights reserved.