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From jinhong lu <lujinho...@gmail.com>
Subject Re: spark to hbase
Date Wed, 28 Oct 2015 01:53:00 GMT
Hi, Ted

thanks for your help.

I check the jar, it is in classpath, and now the problem is :

1、 Follow codes runs good, and it put the  result to hbse:

  val res = lines.map(pairFunction).groupByKey().flatMap(pairFlatMapFunction).aggregateByKey(new
TrainFeature())(seqOp, combOp).values.first()
 val configuration = HBaseConfiguration.create();
  configuration.set("hbase.zookeeper.property.clientPort", "2181");
  configuration.set("hbase.zookeeper.quorum", "192.168.1.66");
  configuration.set("hbase.master", "192.168.1.66:60000");
  val table = new HTable(configuration, "ljh_test3");
  var put = new Put(Bytes.toBytes(res.toKey()));
  put.add(Bytes.toBytes("f"), Bytes.toBytes("c"), Bytes.toBytes(res.positiveCount));
  table.put(put);
  table.flushCommits()

2、But if I change the first() function to foreach:

  lines.map(pairFunction).groupByKey().flatMap(pairFlatMapFunction).aggregateByKey(new TrainFeature())(seqOp,
combOp).values.foreach({res=>
  val configuration = HBaseConfiguration.create();
  configuration.set("hbase.zookeeper.property.clientPort", "2181");
  configuration.set("hbase.zookeeper.quorum", "192.168.1.66");
  configuration.set("hbase.master", "192.168.1.66:60000");
  val table = new HTable(configuration, "ljh_test3");
  var put = new Put(Bytes.toBytes(res.toKey()));
  put.add(Bytes.toBytes("f"), Bytes.toBytes("c"), Bytes.toBytes(res.positiveCount));
  table.put(put);

})

the application hung, and the last log is :

15/10/28 09:30:33 INFO DAGScheduler: Missing parents for ResultStage 2: List()
15/10/28 09:30:33 INFO DAGScheduler: Submitting ResultStage 2 (MapPartitionsRDD[6] at values
at TrainModel3.scala:98), which is now runnable
15/10/28 09:30:33 INFO MemoryStore: ensureFreeSpace(7032) called with curMem=264045, maxMem=278302556
15/10/28 09:30:33 INFO MemoryStore: Block broadcast_3 stored as values in memory (estimated
size 6.9 KB, free 265.2 MB)
15/10/28 09:30:33 INFO MemoryStore: ensureFreeSpace(3469) called with curMem=271077, maxMem=278302556
15/10/28 09:30:33 INFO MemoryStore: Block broadcast_3_piece0 stored as bytes in memory (estimated
size 3.4 KB, free 265.1 MB)
15/10/28 09:30:33 INFO BlockManagerInfo: Added broadcast_3_piece0 in memory on 10.120.69.53:43019
(size: 3.4 KB, free: 265.4 MB)
15/10/28 09:30:33 INFO SparkContext: Created broadcast 3 from broadcast at DAGScheduler.scala:874
15/10/28 09:30:33 INFO DAGScheduler: Submitting 1 missing tasks from ResultStage 2 (MapPartitionsRDD[6]
at values at TrainModel3.scala:98)
15/10/28 09:30:33 INFO YarnScheduler: Adding task set 2.0 with 1 tasks
15/10/28 09:30:33 INFO TaskSetManager: Starting task 0.0 in stage 2.0 (TID 2, gdc-dn147-formal.i.nease.net,
PROCESS_LOCAL, 1716 bytes)
15/10/28 09:30:34 INFO BlockManagerInfo: Added broadcast_3_piece0 in memory on gdc-dn147-formal.i.nease.net:59814
(size: 3.4 KB, free: 1060.3 MB)
15/10/28 09:30:34 INFO MapOutputTrackerMasterEndpoint: Asked to send map output locations
for shuffle 0 to gdc-dn147-formal.i.nease.net:52904
15/10/28 09:30:34 INFO MapOutputTrackerMaster: Size of output statuses for shuffle 0 is 154
bytes

3、besides, I take the configuration and HTable out of foreach:

val configuration = HBaseConfiguration.create();
configuration.set("hbase.zookeeper.property.clientPort", "2181");
configuration.set("hbase.zookeeper.quorum", "192.168.1.66");
configuration.set("hbase.master", "192.168.1.66:60000");
val table = new HTable(configuration, "ljh_test3");

lines.map(pairFunction).groupByKey().flatMap(pairFlatMapFunction).aggregateByKey(new TrainFeature())(seqOp,
combOp).values.foreach({ res =>

  var put = new Put(Bytes.toBytes(res.toKey()));
  put.add(Bytes.toBytes("f"), Bytes.toBytes("c"), Bytes.toBytes(res.positiveCount));
  table.put(put);

})
table.flushCommits()

found serializable problem:

Exception in thread "main" org.apache.spark.SparkException: Task not serializable
        at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:315)
        at org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:305)
        at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:132)
        at org.apache.spark.SparkContext.clean(SparkContext.scala:1891)
        at org.apache.spark.rdd.RDD
$$anonfun$foreach$1.apply(RDD.scala:869)
	        at org.apache.spark.rdd.RDD$$anonfun$foreach$1.apply(RDD.scala:868)
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:148)
        at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:109)
        at org.apache.spark.rdd.RDD.withScope(RDD.scala:286)
        at org.apache.spark.rdd.RDD.foreach(RDD.scala:868)
        at com.chencai.spark.ml.TrainModel3$.train(TrainModel3.scala:100)
        at com.chencai.spark.ml.TrainModel3$.main(TrainModel3.scala:115)
        at com.chencai.spark.ml.TrainModel3.main(TrainModel3.scala)
        at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
        at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
        at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
        at java.lang.reflect.Method.invoke(Method.java:606)
        at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:664)
        at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:169)
        at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:192)
        at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:111)
        at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.io.NotSerializableException: org.apache.hadoop.conf.Configuration
Serialization stack:
        - object not serializable (class: org.apache.hadoop.conf.Configuration, value: Configuration:
core-default.xml, core-site.xml, mapred-default.xml, mapred-site.xml, yarn-default.xml, yarn-site.xml,
hdfs-default.xml, hdfs-site.xml, hbase-default.xml, hbase-site.xml)
        - field (class: com.chencai.spark.ml.TrainModel3$$anonfun$train$5, name: configuration$1,
type: class org.apache.hadoop.conf.Configuration)
	        - object (class com.chencai.spark.ml.TrainModel3$$anonfun$train$5, <function1>)
        at org.apache.spark.serializer.SerializationDebugger$.improveException(SerializationDebugger.scala:40)
        at org.apache.spark.serializer.JavaSerializationStream.writeObject(JavaSerializer.scala:47)
        at org.apache.spark.serializer.JavaSerializerInstance.serialize(JavaSerializer.scala:81)
        at org.apache.spark.util.ClosureCleaner$.ensureSerializable(ClosureCleaner.scala:312)
        ... 21 more




> 在 2015年10月28日,09:26,Ted Yu <yuzhihong@gmail.com> 写道:
> 
> Jinghong:
> In one of earlier threads on storing data to hbase, it was found that htrace jar was
not on classpath, leading to write failure.
> 
> Can you check whether you are facing the same problem ?
> 
> Cheers
> 
> On Tue, Oct 27, 2015 at 5:11 AM, Ted Yu <yuzhihong@gmail.com <mailto:yuzhihong@gmail.com>>
wrote:
> Jinghong:
> Hadmin variable is not used. You can omit that line. 
> 
> Which hbase release are you using ?
> 
> As Deng said, don't flush per row. 
> 
> Cheers
> 
> On Oct 27, 2015, at 3:21 AM, Deng Ching-Mallete <oching@apache.org <mailto:oching@apache.org>>
wrote:
> 
>> Hi,
>> 
>> It would be more efficient if you configure the table and flush the commits by partition
instead of per element in the RDD. The latter works fine because you only have 4 elements,
but it won't bid well for large data sets IMO..
>> 
>> Thanks,
>> Deng
>> 
>> On Tue, Oct 27, 2015 at 5:22 PM, jinhong lu <lujinhong2@gmail.com <mailto:lujinhong2@gmail.com>>
wrote:
>> 
>> 
>> Hi, 
>> 
>> I write my result to hdfs, it did well:
>> 
>> val model = lines.map(pairFunction).groupByKey().flatMap(pairFlatMapFunction).aggregateByKey(new
TrainFeature())(seqOp, combOp).values
>>  model.map(a => (a.toKey() + "\t" + a.totalCount + "\t" + a.positiveCount)).saveAsTextFile(modelDataPath);
>> 
>> But when I want to write to hbase, the applicaton hung, no log, no response, just
stay there, and nothing is written to hbase:
>> 
>> val model = lines.map(pairFunction).groupByKey().flatMap(pairFlatMapFunction).aggregateByKey(new
TrainFeature())(seqOp, combOp).values.foreach({ res =>
>>   val configuration = HBaseConfiguration.create();
>>   configuration.set("hbase.zookeeper.property.clientPort", "2181");
>>   configuration.set("hbase.zookeeper.quorum", “192.168.1.66");
>>   configuration.set("hbase.master", "192.168.1:60000");
>>   val hadmin = new HBaseAdmin(configuration);
>>   val table = new HTable(configuration, "ljh_test3");
>>   var put = new Put(Bytes.toBytes(res.toKey()));
>>   put.add(Bytes.toBytes("f"), Bytes.toBytes("c"), Bytes.toBytes(res.totalCount +
res.positiveCount));
>>   table.put(put);
>>   table.flushCommits()
>> })
>> 
>> And then I try to write som simple data to hbase, it did well too:
>> 
>> sc.parallelize(Array(1,2,3,4)).foreach({ res =>
>> val configuration = HBaseConfiguration.create();
>> configuration.set("hbase.zookeeper.property.clientPort", "2181");
>> configuration.set("hbase.zookeeper.quorum", "192.168.1.66");
>> configuration.set("hbase.master", "192.168.1:60000");
>> val hadmin = new HBaseAdmin(configuration);
>> val table = new HTable(configuration, "ljh_test3");
>> var put = new Put(Bytes.toBytes(res));
>> put.add(Bytes.toBytes("f"), Bytes.toBytes("c"), Bytes.toBytes(res));
>> table.put(put);
>> table.flushCommits()
>> })
>> 
>> what is the problem with the 2rd code? thanks a lot.
>> 
>> 
> 


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