subject:"got Warn message \- \"the expected leader session ID did not equal the received leader session ID \" when using LocalFlinkMiniCluster to interpret scala code"

Re: got Warn message - "the expected leader session ID did not equal the received leader session ID " when using LocalFlinkMiniCluster to interpret scala code

2017-10-11 Thread Aljoscha Krettek

Hi,

I think you can make it start the Web Frontend via

conf.setBoolean(ConfigConstants.LOCAL_START_WEBSERVER, true);

In the future, this will become moot, though, when the JobManager has a proper 
REST API that is always there.

Best,
Aljoscha


> On 27. Sep 2017, at 11:40, XiangWei Huang  wrote:
> 
> Hi Till,
>   
>   I’ve found that a StandaloneMiniCluster doesn’t startup web fronted 
> when it is running.so,how can i cancel a running job on it with restful 
> method.
> 
> Cheers,
> Till
> 
>> 在 2017年9月20日，15:43，Till Rohrmann  写道：
>> 
>> Hi XiangWei,
>> 
>> programmatically there is no nice tooling yet to cancel jobs on a dedicated 
>> cluster. What you can do is to use Flink's REST API to issue a cancel 
>> command [1]. You have to send a GET request to the target URL 
>> `/jobs/:jobid/cancel`. In the future we will improve the programmatic job 
>> control which will allow you to do these kind of things more easily.
>> 
>> [1] 
>> https://ci.apache.org/projects/flink/flink-docs-release-1.3/monitoring/rest_api.html#job-cancellation
>> 
>> Cheers,
>> Till
>> 
>> On Wed, Sep 20, 2017 at 5:46 AM, XiangWei Huang  
>> wrote:
>> Hi Till,
>>
>>  Thanks for your answer,it worked when i use StandaloneMiniCluster,but 
>> another problem is that i can’t find a way to cancel
>> a running Flink job without shutting down the cluster,for 
>> LocalFlinkMiniCluster i can do  it with below code :
>> 
>>for (job <- cluster.getCurrentlyRunningJobsJava()) {
>>   cluster.stopJob(job)
>>}
>> 
>>Is it possible to cancel a running Flink job without shutting down a 
>> StandaloneMiniCluster ?
>> 
>> Best Regards,
>> XiangWei
>> 
>> 
>> 
>>> 在 2017年9月14日，16:58，Till Rohrmann  写道：
>>> 
>>> Hi XiangWei,
>>> 
>>> the problem is that the LocalFlinkMiniCluster can no longer be used in 
>>> combination with a RemoteExecutionEnvironment. The reason is that the 
>>> LocalFlinkMiniCluster uses now an internal leader election service and 
>>> assigns leader ids to its components. Since this is an internal service it 
>>> is not possible to retrieve this information like it is the case with the 
>>> ZooKeeper based leader election services.
>>> 
>>> Long story short, the Flink Scala shell currently does not work with a 
>>> LocalFlinkMiniCluster and would have to be fixed to work properly together 
>>> with a local execution environment. Until then, I recommend starting a 
>>> local standalone cluster and let the code run there.
>>> 
>>> Cheers,
>>> Till
>>> 
>>> 
>>> On Wed, Sep 13, 2017 at 6:21 AM, XiangWei Huang  
>>> wrote:
>>> dear all,
>>> 
>>> Below is the code i execute:
>>> 
>>> import java.io._
>>> import java.net.{URL, URLClassLoader}
>>> import java.nio.charset.Charset
>>> import java.util.Collections
>>> import java.util.concurrent.atomic.AtomicBoolean
>>> 
>>> import com.netease.atom.common.util.logging.Logging
>>> import com.netease.atom.interpreter.Code.Code
>>> import com.netease.atom.interpreter.{Code, Interpreter, InterpreterResult, 
>>> InterpreterUtils}
>>> import io.netty.buffer._
>>> import org.apache.flink.api.scala.FlinkILoop
>>> import org.apache.flink.client.CliFrontend
>>> import org.apache.flink.client.cli.CliFrontendParser
>>> import org.apache.flink.client.program.ClusterClient
>>> import org.apache.flink.configuration.{QueryableStateOptions, 
>>> Configuration, ConfigConstants, GlobalConfiguration}
>>> import org.apache.flink.runtime.akka.AkkaUtils
>>> import org.apache.flink.runtime.minicluster.{StandaloneMiniCluster, 
>>> LocalFlinkMiniCluster}
>>> 
>>> import scala.Console
>>> import scala.beans.BeanProperty
>>> import scala.collection.JavaConversions._
>>> import scala.collection.mutable
>>> import scala.collection.mutable.{ArrayBuffer, ListBuffer}
>>> import scala.runtime.AbstractFunction0
>>> import scala.tools.nsc.Settings
>>> import scala.tools.nsc.interpreter.{IMain, JPrintWriter, Results}
>>> 
>>> class FlinkInterpreter extends Interpreter {
>>>   private var bufferedReader: Option[BufferedReader] = None
>>>   private var jprintWriter: JPrintWriter = _
>>>   private val config = new Configuration;
>>>   private var cluster: LocalFlinkMiniCluster = _
>>>   @BeanProperty var imain: IMain = _
>>>   @BeanProperty var flinkILoop: FlinkILoop = _
>>>   private var out: ByteBufOutputStream = null
>>>   private var outBuf: ByteBuf = null
>>>   private var in: ByteBufInputStream = _
>>>   private var isRunning: AtomicBoolean = new AtomicBoolean(false)
>>> 
>>>   override def isOpen: Boolean = {
>>> isRunning.get()
>>>   }
>>> 
>>>   def startLocalMiniCluster(): (String, Int, LocalFlinkMiniCluster) = {
>>> config.toMap.toMap.foreach(println)
>>> config.setInteger(ConfigConstants.LOCAL_NUMBER_JOB_MANAGER, 1)
>>> config.setInteger(ConfigConstants.LOCAL_NUMBER_TASK_MANAGER, 1)
>>> config.setInteger(ConfigConstants.LOCAL_NUMBER_RESOURCE_MANAGER, 1)

Re: got Warn message - "the expected leader session ID did not equal the received leader session ID " when using LocalFlinkMiniCluster to interpret scala code

2017-09-27 Thread XiangWei Huang

Hi Till,

I’ve found that a StandaloneMiniCluster doesn’t startup web fronted 
when it is running.so,how can i cancel a running job on it with restful method.

Cheers,
Till

> 在 2017年9月20日，15:43，Till Rohrmann  写道：
> 
> Hi XiangWei,
> 
> programmatically there is no nice tooling yet to cancel jobs on a dedicated 
> cluster. What you can do is to use Flink's REST API to issue a cancel command 
> [1]. You have to send a GET request to the target URL `/jobs/:jobid/cancel`. 
> In the future we will improve the programmatic job control which will allow 
> you to do these kind of things more easily.
> 
> [1] 
> https://ci.apache.org/projects/flink/flink-docs-release-1.3/monitoring/rest_api.html#job-cancellation
>  
> 
> 
> Cheers,
> Till
> 
> On Wed, Sep 20, 2017 at 5:46 AM, XiangWei Huang  > wrote:
> Hi Till,
>
>  Thanks for your answer,it worked when i use StandaloneMiniCluster,but 
> another problem is that i can’t find a way to cancel
> a running Flink job without shutting down the cluster,for 
> LocalFlinkMiniCluster i can do  it with below code :
> 
>for (job <- cluster.getCurrentlyRunningJobsJava()) {
>   cluster.stopJob(job)
>}
> 
>Is it possible to cancel a running Flink job without shutting down a 
> StandaloneMiniCluster ?
> 
> Best Regards,
> XiangWei
> 
> 
> 
>> 在 2017年9月14日，16:58，Till Rohrmann > > 写道：
>> 
>> Hi XiangWei,
>> 
>> the problem is that the LocalFlinkMiniCluster can no longer be used in 
>> combination with a RemoteExecutionEnvironment. The reason is that the 
>> LocalFlinkMiniCluster uses now an internal leader election service and 
>> assigns leader ids to its components. Since this is an internal service it 
>> is not possible to retrieve this information like it is the case with the 
>> ZooKeeper based leader election services.
>> 
>> Long story short, the Flink Scala shell currently does not work with a 
>> LocalFlinkMiniCluster and would have to be fixed to work properly together 
>> with a local execution environment. Until then, I recommend starting a local 
>> standalone cluster and let the code run there.
>> 
>> Cheers,
>> Till
>> 
>> 
>> On Wed, Sep 13, 2017 at 6:21 AM, XiangWei Huang > > wrote:
>> dear all,
>> 
>> Below is the code i execute:
>> 
>> import java.io ._
>> import java.net .{URL, URLClassLoader}
>> import java.nio.charset.Charset
>> import java.util.Collections
>> import java.util.concurrent.at 
>> omic.AtomicBoolean
>> 
>> import com.netease.atom.common.util.logging.Logging
>> import com.netease.atom.interpreter.Code.Code
>> import com.netease.atom.interpreter.{Code, Interpreter, InterpreterResult, 
>> InterpreterUtils}
>> import io.netty.buffer._
>> import org.apache.flink.api.sc 
>> ala.FlinkILoop
>> import org.apache.flink.client.CliFrontend
>> import org.apache.flink.client.cli.CliFrontendParser
>> import org.apache.flink.client.program.ClusterClient
>> import org.apache.flink.configuration.{QueryableStateOptions, Configuration, 
>> ConfigConstants, GlobalConfiguration}
>> import org.apache.flink.runtime.akka.AkkaUtils
>> import org.apache.flink.runtime.minicluster.{StandaloneMiniCluster, 
>> LocalFlinkMiniCluster}
>> 
>> import scala.Console
>> import scala.beans.BeanProperty
>> import scala.collection.JavaConversions._
>> import scala.collection.mutable
>> import scala.collection.mutable.{ArrayBuffer, ListBuffer}
>> import scala.runtime.AbstractFunction0
>> import scala.tools.nsc.Settings
>> import scala.tools.nsc.interpreter.{IMain, JPrintWriter, Results}
>> 
>> class FlinkInterpreter extends Interpreter {
>>   private var bufferedReader: Option[BufferedReader] = None
>>   private var jprintWriter: JPrintWriter = _
>>   private val config = new Configuration;
>>   private var cluster: LocalFlinkMiniCluster = _
>>   @BeanProperty var imain: IMain = _
>>   @BeanProperty var flinkILoop: FlinkILoop = _
>>   private var out: ByteBufOutputStream = null
>>   private var outBuf: ByteBuf = null
>>   private var in: ByteBufInputStream = _
>>   private var isRunning: AtomicBoolean = new AtomicBoolean(false)
>> 
>>   override def isOpen: Boolean = {
>> isRunning.get()
>>   }
>> 
>>   def startLocalMiniCluster(): (String, Int, LocalFlinkMiniCluster) = {
>> config.toMap.toMap.foreach(println)
>> config.setInteger(ConfigConstants.LOCAL_NUMBER_JOB_MANAGER, 1)
>> config.setInteger(ConfigConstants.LOCAL_NUMBER_TASK_MANAGER, 1)
>> config.setInteger(ConfigConstants.LOCAL_NUMBER_RESOURCE_MANAGER, 1)
>> config.setInteger(ConfigConstants.JOB_MANAGER_IPC_PORT_KEY, 0)
>> config.setBoolean(QueryableStateOptions.SERVER_ENABLE.key(),

Re: got Warn message - "the expected leader session ID did not equal the received leader session ID " when using LocalFlinkMiniCluster to interpret scala code

2017-09-20 Thread Till Rohrmann

Hi XiangWei,

programmatically there is no nice tooling yet to cancel jobs on a dedicated
cluster. What you can do is to use Flink's REST API to issue a cancel
command [1]. You have to send a GET request to the target URL
`/jobs/:jobid/cancel`. In the future we will improve the programmatic job
control which will allow you to do these kind of things more easily.

[1]
https://ci.apache.org/projects/flink/flink-docs-release-1.3/monitoring/rest_api.html#job-cancellation

Cheers,
Till

On Wed, Sep 20, 2017 at 5:46 AM, XiangWei Huang 
wrote:

> Hi Till,
>
>  Thanks for your answer,it worked when i use *StandaloneMiniCluster,*
> but another problem is that i can’t find a way to cancel
> a running Flink job without shutting down the cluster,for
> LocalFlinkMiniCluster i can do  it with below code :
>
> *   for (job <- cluster.getCurrentlyRunningJobsJava()) {*
>
> *  cluster.stopJob(job)   }*
>
>Is it possible to cancel a running Flink job without shutting down a 
> *StandaloneMiniCluster
> ?*
>
> Best Regards,
> XiangWei
>
>
>
> 在 2017年9月14日，16:58，Till Rohrmann  写道：
>
> Hi XiangWei,
>
> the problem is that the LocalFlinkMiniCluster can no longer be used in
> combination with a RemoteExecutionEnvironment. The reason is that the
> LocalFlinkMiniCluster uses now an internal leader election service and
> assigns leader ids to its components. Since this is an internal service it
> is not possible to retrieve this information like it is the case with the
> ZooKeeper based leader election services.
>
> Long story short, the Flink Scala shell currently does not work with a
> LocalFlinkMiniCluster and would have to be fixed to work properly
> together with a local execution environment. Until then, I recommend
> starting a local standalone cluster and let the code run there.
>
> Cheers,
> Till
> 
>
> On Wed, Sep 13, 2017 at 6:21 AM, XiangWei Huang 
> wrote:
>
>> dear all,
>>
>> *Below is the code i execute:*
>>
>> import java.io._
>> import java.net.{URL, URLClassLoader}
>> import java.nio.charset.Charset
>> import java.util.Collections
>> import java.util.concurrent.atomic.AtomicBoolean
>>
>> import com.netease.atom.common.util.logging.Logging
>> import com.netease.atom.interpreter.Code.Code
>> import com.netease.atom.interpreter.{Code, Interpreter, Inte
>> rpreterResult, InterpreterUtils}
>> import io.netty.buffer._
>> import org.apache.flink.api.scala.FlinkILoop
>> import org.apache.flink.client.CliFrontend
>> import org.apache.flink.client.cli.CliFrontendParser
>> import org.apache.flink.client.program.ClusterClient
>> import org.apache.flink.configuration.{QueryableStateOptions
>> , Configuration, ConfigConstants, GlobalConfiguration}
>> import org.apache.flink.runtime.akka.AkkaUtils
>> import org.apache.flink.runtime.minicluster.{StandaloneMiniC
>> luster, LocalFlinkMiniCluster}
>>
>> import scala.Console
>> import scala.beans.BeanProperty
>> import scala.collection.JavaConversions._
>> import scala.collection.mutable
>> import scala.collection.mutable.{ArrayBuffer, ListBuffer}
>> import scala.runtime.AbstractFunction0
>> import scala.tools.nsc.Settings
>> import scala.tools.nsc.interpreter.{IMain, JPrintWriter, Results}
>>
>> class FlinkInterpreter extends Interpreter {
>>   private var bufferedReader: Option[BufferedReader] = None
>>   private var jprintWriter: JPrintWriter = _
>>   private val config = new Configuration;
>>   private var cluster: LocalFlinkMiniCluster = _
>>   @BeanProperty var imain: IMain = _
>>   @BeanProperty var flinkILoop: FlinkILoop = _
>>   private var out: ByteBufOutputStream = null
>>   private var outBuf: ByteBuf = null
>>   private var in: ByteBufInputStream = _
>>   private var isRunning: AtomicBoolean = new AtomicBoolean(false)
>>
>>   override def isOpen: Boolean = {
>> isRunning.get()
>>   }
>>
>>   def startLocalMiniCluster(): (String, Int, LocalFlinkMiniCluster) = {
>> config.toMap.toMap.foreach(println)
>> config.setInteger(ConfigConstants.LOCAL_NUMBER_JOB_MANAGER, 1)
>> config.setInteger(ConfigConstants.LOCAL_NUMBER_TASK_MANAGER, 1)
>> config.setInteger(ConfigConstants.LOCAL_NUMBER_RESOURCE_MANAGER, 1)
>> config.setInteger(ConfigConstants.JOB_MANAGER_IPC_PORT_KEY, 0)
>> config.setBoolean(QueryableStateOptions.SERVER_ENABLE.key(), true)
>> config.setBoolean(ConfigConstants.LOCAL_START_WEBSERVER, true)
>> val localCluster = new LocalFlinkMiniCluster(config, false)
>> localCluster.start(true)
>> val port = AkkaUtils.getAddress(localCluster.jobManagerActorSystems.
>> get.head).port
>> println(s"Starting local Flink cluster (host:
>> localhost,port: ${localCluster.getLeaderRPCPort}).\n")
>> ("localhost", localCluster.getLeaderRPCPort, localCluster)
>>   }
>>
>>
>>   /**
>>* Start flink cluster and create interpreter
>>*/
>>   override def open: Unit = {
>> outBuf = ByteBufAllocator.DEFAULT.heapBuffer(20480)
>> out = new

Re: got Warn message - "the expected leader session ID did not equal the received leader session ID " when using LocalFlinkMiniCluster to interpret scala code

2017-09-19 Thread XiangWei Huang

Hi Till,
   
 Thanks for your answer,it worked when i use StandaloneMiniCluster,but 
another problem is that i can’t find a way to cancel
a running Flink job without shutting down the cluster,for LocalFlinkMiniCluster 
i can do  it with below code :

   for (job <- cluster.getCurrentlyRunningJobsJava()) {
  cluster.stopJob(job)
   }

   Is it possible to cancel a running Flink job without shutting down a 
StandaloneMiniCluster ?

Best Regards,
XiangWei



> 在 2017年9月14日，16:58，Till Rohrmann  写道：
> 
> Hi XiangWei,
> 
> the problem is that the LocalFlinkMiniCluster can no longer be used in 
> combination with a RemoteExecutionEnvironment. The reason is that the 
> LocalFlinkMiniCluster uses now an internal leader election service and 
> assigns leader ids to its components. Since this is an internal service it is 
> not possible to retrieve this information like it is the case with the 
> ZooKeeper based leader election services.
> 
> Long story short, the Flink Scala shell currently does not work with a 
> LocalFlinkMiniCluster and would have to be fixed to work properly together 
> with a local execution environment. Until then, I recommend starting a local 
> standalone cluster and let the code run there.
> 
> Cheers,
> Till
> 
> 
> On Wed, Sep 13, 2017 at 6:21 AM, XiangWei Huang  > wrote:
> dear all,
> 
> Below is the code i execute:
> 
> import java.io ._
> import java.net .{URL, URLClassLoader}
> import java.nio.charset.Charset
> import java.util.Collections
> import java.util.concurrent.atomic.AtomicBoolean
> 
> import com.netease.atom.common.util.logging.Logging
> import com.netease.atom.interpreter.Code.Code
> import com.netease.atom.interpreter.{Code, Interpreter, InterpreterResult, 
> InterpreterUtils}
> import io.netty.buffer._
> import org.apache.flink.api.scala.FlinkILoop
> import org.apache.flink.client.CliFrontend
> import org.apache.flink.client.cli.CliFrontendParser
> import org.apache.flink.client.program.ClusterClient
> import org.apache.flink.configuration.{QueryableStateOptions, Configuration, 
> ConfigConstants, GlobalConfiguration}
> import org.apache.flink.runtime.akka.AkkaUtils
> import org.apache.flink.runtime.minicluster.{StandaloneMiniCluster, 
> LocalFlinkMiniCluster}
> 
> import scala.Console
> import scala.beans.BeanProperty
> import scala.collection.JavaConversions._
> import scala.collection.mutable
> import scala.collection.mutable.{ArrayBuffer, ListBuffer}
> import scala.runtime.AbstractFunction0
> import scala.tools.nsc.Settings
> import scala.tools.nsc.interpreter.{IMain, JPrintWriter, Results}
> 
> class FlinkInterpreter extends Interpreter {
>   private var bufferedReader: Option[BufferedReader] = None
>   private var jprintWriter: JPrintWriter = _
>   private val config = new Configuration;
>   private var cluster: LocalFlinkMiniCluster = _
>   @BeanProperty var imain: IMain = _
>   @BeanProperty var flinkILoop: FlinkILoop = _
>   private var out: ByteBufOutputStream = null
>   private var outBuf: ByteBuf = null
>   private var in: ByteBufInputStream = _
>   private var isRunning: AtomicBoolean = new AtomicBoolean(false)
> 
>   override def isOpen: Boolean = {
> isRunning.get()
>   }
> 
>   def startLocalMiniCluster(): (String, Int, LocalFlinkMiniCluster) = {
> config.toMap.toMap.foreach(println)
> config.setInteger(ConfigConstants.LOCAL_NUMBER_JOB_MANAGER, 1)
> config.setInteger(ConfigConstants.LOCAL_NUMBER_TASK_MANAGER, 1)
> config.setInteger(ConfigConstants.LOCAL_NUMBER_RESOURCE_MANAGER, 1)
> config.setInteger(ConfigConstants.JOB_MANAGER_IPC_PORT_KEY, 0)
> config.setBoolean(QueryableStateOptions.SERVER_ENABLE.key(), true)
> config.setBoolean(ConfigConstants.LOCAL_START_WEBSERVER, true)
> val localCluster = new LocalFlinkMiniCluster(config, false)
> localCluster.start(true)
> val port = 
> AkkaUtils.getAddress(localCluster.jobManagerActorSystems.get.head).port
> println(s"Starting local Flink cluster (host: localhost,port: 
> ${localCluster.getLeaderRPCPort}).\n")
> ("localhost", localCluster.getLeaderRPCPort, localCluster)
>   }
> 
>  
>   /**
>* Start flink cluster and create interpreter
>*/
>   override def open: Unit = {
> outBuf = ByteBufAllocator.DEFAULT.heapBuffer(20480)
> out = new ByteBufOutputStream(outBuf)
> in = new ByteBufInputStream(outBuf)
> //val (host, port, yarnCluster) = 
> deployNewYarnCluster(YarnConfig(Option(1), None, None, None, Option(1), None))
> val (host, port, localCluster) = startLocalMiniCluster()
> this.cluster = localCluster
> val conf = cluster.configuration
> println(s"Connecting to Flink cluster (host:$host,port:$port)...")
> flinkILoop = new FlinkILoop(host, port, conf, None)
> val settings = new Settings()
> settings.usejavacp.value = true
> settings.Yreplsync.value = true
>

Re: got Warn message - "the expected leader session ID did not equal the received leader session ID " when using LocalFlinkMiniCluster to interpret scala code

2017-09-14 Thread Till Rohrmann

Hi XiangWei,

the problem is that the LocalFlinkMiniCluster can no longer be used in
combination with a RemoteExecutionEnvironment. The reason is that the
LocalFlinkMiniCluster uses now an internal leader election service and
assigns leader ids to its components. Since this is an internal service it
is not possible to retrieve this information like it is the case with the
ZooKeeper based leader election services.

Long story short, the Flink Scala shell currently does not work with a
LocalFlinkMiniCluster and would have to be fixed to work properly together
with a local execution environment. Until then, I recommend starting a
local standalone cluster and let the code run there.

Cheers,
Till


On Wed, Sep 13, 2017 at 6:21 AM, XiangWei Huang 
wrote:

> dear all,
>
> *Below is the code i execute:*
>
> import java.io._
> import java.net.{URL, URLClassLoader}
> import java.nio.charset.Charset
> import java.util.Collections
> import java.util.concurrent.atomic.AtomicBoolean
>
> import com.netease.atom.common.util.logging.Logging
> import com.netease.atom.interpreter.Code.Code
> import com.netease.atom.interpreter.{Code, Interpreter,
> InterpreterResult, InterpreterUtils}
> import io.netty.buffer._
> import org.apache.flink.api.scala.FlinkILoop
> import org.apache.flink.client.CliFrontend
> import org.apache.flink.client.cli.CliFrontendParser
> import org.apache.flink.client.program.ClusterClient
> import org.apache.flink.configuration.{QueryableStateOptions,
> Configuration, ConfigConstants, GlobalConfiguration}
> import org.apache.flink.runtime.akka.AkkaUtils
> import org.apache.flink.runtime.minicluster.{StandaloneMiniCluster,
> LocalFlinkMiniCluster}
>
> import scala.Console
> import scala.beans.BeanProperty
> import scala.collection.JavaConversions._
> import scala.collection.mutable
> import scala.collection.mutable.{ArrayBuffer, ListBuffer}
> import scala.runtime.AbstractFunction0
> import scala.tools.nsc.Settings
> import scala.tools.nsc.interpreter.{IMain, JPrintWriter, Results}
>
> class FlinkInterpreter extends Interpreter {
>   private var bufferedReader: Option[BufferedReader] = None
>   private var jprintWriter: JPrintWriter = _
>   private val config = new Configuration;
>   private var cluster: LocalFlinkMiniCluster = _
>   @BeanProperty var imain: IMain = _
>   @BeanProperty var flinkILoop: FlinkILoop = _
>   private var out: ByteBufOutputStream = null
>   private var outBuf: ByteBuf = null
>   private var in: ByteBufInputStream = _
>   private var isRunning: AtomicBoolean = new AtomicBoolean(false)
>
>   override def isOpen: Boolean = {
> isRunning.get()
>   }
>
>   def startLocalMiniCluster(): (String, Int, LocalFlinkMiniCluster) = {
> config.toMap.toMap.foreach(println)
> config.setInteger(ConfigConstants.LOCAL_NUMBER_JOB_MANAGER, 1)
> config.setInteger(ConfigConstants.LOCAL_NUMBER_TASK_MANAGER, 1)
> config.setInteger(ConfigConstants.LOCAL_NUMBER_RESOURCE_MANAGER, 1)
> config.setInteger(ConfigConstants.JOB_MANAGER_IPC_PORT_KEY, 0)
> config.setBoolean(QueryableStateOptions.SERVER_ENABLE.key(), true)
> config.setBoolean(ConfigConstants.LOCAL_START_WEBSERVER, true)
> val localCluster = new LocalFlinkMiniCluster(config, false)
> localCluster.start(true)
> val port = AkkaUtils.getAddress(localCluster.
> jobManagerActorSystems.get.head).port
> println(s"Starting local Flink cluster (host: localhost,port: ${
> localCluster.getLeaderRPCPort}).\n")
> ("localhost", localCluster.getLeaderRPCPort, localCluster)
>   }
>
>
>   /**
>* Start flink cluster and create interpreter
>*/
>   override def open: Unit = {
> outBuf = ByteBufAllocator.DEFAULT.heapBuffer(20480)
> out = new ByteBufOutputStream(outBuf)
> in = new ByteBufInputStream(outBuf)
> //val (host, port, yarnCluster) = 
> deployNewYarnCluster(YarnConfig(Option(1),
> None, None, None, Option(1), None))
> val (host, port, localCluster) = startLocalMiniCluster()
> this.cluster = localCluster
> val conf = cluster.configuration
> println(s"Connecting to Flink cluster (host:$host,port:$port)...")
> flinkILoop = new FlinkILoop(host, port, conf, None)
> val settings = new Settings()
> settings.usejavacp.value = true
> settings.Yreplsync.value = true
> flinkILoop.settings_$eq(settings)
> flinkILoop.createInterpreter()
> imain = flinkILoop.intp
> FlinkInterpreter.ourClassloader = imain.classLoader
> val benv = flinkILoop.scalaBenv
> val senv = flinkILoop.scalaSenv
> benv.getConfig.disableSysoutLogging()
> senv.getConfig.disableSysoutLogging()
> // import libraries
> imain.interpret("import scala.tools.nsc.io._")
> //imain.interpret("import Properties.userHome")
> imain.interpret("import scala.compat.Platform.EOL")
> imain.interpret("import org.apache.flink.api.scala._")
> imain.interpret("import org.apache.flink.api.common.functions._")
> isRunning.set(true)
>

got Warn message - "the expected leader session ID did not equal the received leader session ID " when using LocalFlinkMiniCluster to interpret scala code

2017-09-12 Thread XiangWei Huang

dear all,

Below is the code i execute:

import java.io._
import java.net.{URL, URLClassLoader}
import java.nio.charset.Charset
import java.util.Collections
import java.util.concurrent.atomic.AtomicBoolean

import com.netease.atom.common.util.logging.Logging
import com.netease.atom.interpreter.Code.Code
import com.netease.atom.interpreter.{Code, Interpreter, InterpreterResult, 
InterpreterUtils}
import io.netty.buffer._
import org.apache.flink.api.scala.FlinkILoop
import org.apache.flink.client.CliFrontend
import org.apache.flink.client.cli.CliFrontendParser
import org.apache.flink.client.program.ClusterClient
import org.apache.flink.configuration.{QueryableStateOptions, Configuration, 
ConfigConstants, GlobalConfiguration}
import org.apache.flink.runtime.akka.AkkaUtils
import org.apache.flink.runtime.minicluster.{StandaloneMiniCluster, 
LocalFlinkMiniCluster}

import scala.Console
import scala.beans.BeanProperty
import scala.collection.JavaConversions._
import scala.collection.mutable
import scala.collection.mutable.{ArrayBuffer, ListBuffer}
import scala.runtime.AbstractFunction0
import scala.tools.nsc.Settings
import scala.tools.nsc.interpreter.{IMain, JPrintWriter, Results}

class FlinkInterpreter extends Interpreter {
  private var bufferedReader: Option[BufferedReader] = None
  private var jprintWriter: JPrintWriter = _
  private val config = new Configuration;
  private var cluster: LocalFlinkMiniCluster = _
  @BeanProperty var imain: IMain = _
  @BeanProperty var flinkILoop: FlinkILoop = _
  private var out: ByteBufOutputStream = null
  private var outBuf: ByteBuf = null
  private var in: ByteBufInputStream = _
  private var isRunning: AtomicBoolean = new AtomicBoolean(false)

  override def isOpen: Boolean = {
isRunning.get()
  }

  def startLocalMiniCluster(): (String, Int, LocalFlinkMiniCluster) = {
config.toMap.toMap.foreach(println)
config.setInteger(ConfigConstants.LOCAL_NUMBER_JOB_MANAGER, 1)
config.setInteger(ConfigConstants.LOCAL_NUMBER_TASK_MANAGER, 1)
config.setInteger(ConfigConstants.LOCAL_NUMBER_RESOURCE_MANAGER, 1)
config.setInteger(ConfigConstants.JOB_MANAGER_IPC_PORT_KEY, 0)
config.setBoolean(QueryableStateOptions.SERVER_ENABLE.key(), true)
config.setBoolean(ConfigConstants.LOCAL_START_WEBSERVER, true)
val localCluster = new LocalFlinkMiniCluster(config, false)
localCluster.start(true)
val port = 
AkkaUtils.getAddress(localCluster.jobManagerActorSystems.get.head).port
println(s"Starting local Flink cluster (host: localhost,port: 
${localCluster.getLeaderRPCPort}).\n")
("localhost", localCluster.getLeaderRPCPort, localCluster)
  }

 
  /**
   * Start flink cluster and create interpreter
   */
  override def open: Unit = {
outBuf = ByteBufAllocator.DEFAULT.heapBuffer(20480)
out = new ByteBufOutputStream(outBuf)
in = new ByteBufInputStream(outBuf)
//val (host, port, yarnCluster) = 
deployNewYarnCluster(YarnConfig(Option(1), None, None, None, Option(1), None))
val (host, port, localCluster) = startLocalMiniCluster()
this.cluster = localCluster
val conf = cluster.configuration
println(s"Connecting to Flink cluster (host:$host,port:$port)...")
flinkILoop = new FlinkILoop(host, port, conf, None)
val settings = new Settings()
settings.usejavacp.value = true
settings.Yreplsync.value = true
flinkILoop.settings_$eq(settings)
flinkILoop.createInterpreter()
imain = flinkILoop.intp
FlinkInterpreter.ourClassloader = imain.classLoader
val benv = flinkILoop.scalaBenv
val senv = flinkILoop.scalaSenv
benv.getConfig.disableSysoutLogging()
senv.getConfig.disableSysoutLogging()
// import libraries
imain.interpret("import scala.tools.nsc.io._")
//imain.interpret("import Properties.userHome")
imain.interpret("import scala.compat.Platform.EOL")
imain.interpret("import org.apache.flink.api.scala._")
imain.interpret("import org.apache.flink.api.common.functions._")
isRunning.set(true)
  }

  override def interpret(line: String): InterpreterResult = {
if (line == null || line.trim.length == 0) {
  return new InterpreterResult(Code.SUCCESS)
}
interpret(line.split("\n"))
  }

  /**
   * Interprete code
   * @param lines
   * @return
   */
  def interpret(lines: Array[String]): InterpreterResult = {
val imain: IMain = getImain
val linesToRun: Array[String] = new Array[String](lines.length + 1)
for (i <- 0 until lines.length) {
  linesToRun(i) = lines(i)
}
linesToRun(lines.length) = "print(\"\")"
System.setOut(new PrintStream(out))
out.buffer().clear()
var r: Code = null
var incomplete: String = ""
var inComment: Boolean = false
for (l <- 0 until linesToRun.length) {
  val s: String = linesToRun(l)
  var continuation: Boolean = false
  if (l + 1 < linesToRun.length) {
val nextLine: String = linesToRun(l + 1).trim
if (nextLine.isEmpty ||

Re: got Warn message - "the expected leader session ID did not equal the received leader session ID " when using LocalFlinkMiniCluster to interpret scala code

Re: got Warn message - "the expected leader session ID did not equal the received leader session ID " when using LocalFlinkMiniCluster to interpret scala code

Re: got Warn message - "the expected leader session ID did not equal the received leader session ID " when using LocalFlinkMiniCluster to interpret scala code

Re: got Warn message - "the expected leader session ID did not equal the received leader session ID " when using LocalFlinkMiniCluster to interpret scala code

Re: got Warn message - "the expected leader session ID did not equal the received leader session ID " when using LocalFlinkMiniCluster to interpret scala code

got Warn message - "the expected leader session ID did not equal the received leader session ID " when using LocalFlinkMiniCluster to interpret scala code

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