Thank you Gen, the changes to HBaseConverters.scala look to now be returning
all column qualifiers, as follows -
(u'row1', {u'qualifier': u'a', u'timestamp': u'1438716994027', u'value':
u'value1', u'columnFamily': u'f1', u'type': u'Put', u'row': u'row1'})
(u'row1', {u'qualifier': u'b', u'timestamp': u'1438717004248', u'value':
u'value2', u'columnFamily': u'f1', u'type': u'Put', u'row': u'row1'})
(u'row2', {u'qualifier': u'', u'timestamp': u'1438717014529', u'value':
u'value3', u'columnFamily': u'f1', u'type': u'Put', u'row': u'row2'})
(u'row3', {u'qualifier': u'', u'timestamp': u'1438717022756', u'value':
u'value4', u'columnFamily': u'f1', u'type': u'Put', u'row': u'row3'})
Just to be clear, you refer to "Spark update these two scripts recently.". What
two scripts were you referencing?
On Friday, August 7, 2015 7:59 PM, gen tang <gen.tan...@gmail.com> wrote:
Hi,
In fact, Pyspark use
org.apache.spark.examples.pythonconverters(./examples/src/main/scala/org/apache/spark/pythonconverters/)
to transform object of Hbase result to python string.Spark update these two
scripts recently. However, they are not included in the official release of
spark. So you are trying to use this new python script with old jar.
You can clone the newest code of spark from github and build examples jar. Then
you can get correct result.
CheersGen
On Sat, Aug 8, 2015 at 5:03 AM, Eric Bless <eric.bl...@yahoo.com.invalid> wrote:
I’m having some difficulty getting the desired results fromthe Spark Python
example hbase_inputformat.py. I’m running with CDH5.4, hbaseVersion 1.0.0,
Spark v 1.3.0 Using Python version 2.6.6 I followed the example to create a
test HBase table. Here’sthe data from the table I created – hbase(main):001:0>
scan 'dev_wx_test'ROW COLUMN+CELLrow1
column=f1:a, timestamp=1438716994027, value=value1row1
column=f1:b, timestamp=1438717004248, value=value2row2
column=f1:, timestamp=1438717014529, value=value3row3
column=f1:, timestamp=1438717022756, value=value43 row(s) in 0.2620 seconds
When either of these statements are included -“hbase_rdd =
hbase_rdd.flatMapValues(lambda v:v.split("\n"))” or “hbase_rdd =
hbase_rdd.flatMapValues(lambda v:v.split("\n")).countByValue().items()” the
result is - We only get the following printed; (row1, value2) is notprinted:
((u'row1', u'value1'), 1) ((u'row2', u'value3'), 1)
((u'row3', u'value4'), 1) This looks like similar results to the following post
Ifound
-http://apache-spark-user-list.1001560.n3.nabble.com/pyspark-get-column-family-and-qualifier-names-from-hbase-table-td18613.html#a18650but
it appears the pythonconverterHBaseResultToStringConverter has been updated
since then.
And this problem will be resolved too.
When the statement “hbase_rdd = hbase_rdd.flatMapValues(lambda
v:v.split("\n")).mapValues(json.loads)” is included, the result is –
ValueError: No JSON object could be decoded
**************************************************************************************
Here is more info on this from the log – Traceback (most recent call last):
File"hbase_inputformat.py", line 87, in <module> output =hbase_rdd.collect()
File"/opt/cloudera/parcels/CDH-5.4.0-1.cdh5.4.0.p0.27/jars/spark-assembly-1.3.0-cdh5.4.0-hadoop2.6.0-cdh5.4.0.jar/pyspark/rdd.py",line
701, in collect
File"/opt/cloudera/parcels/CDH-5.4.0-1.cdh5.4.0.p0.27/jars/spark-assembly-1.3.0-cdh5.4.0-hadoop2.6.0-cdh5.4.0.jar/py4j/java_gateway.py",line
538, in __call__ File
"/opt/cloudera/parcels/CDH-5.4.0-1.cdh5.4.0.p0.27/jars/spark-assembly-1.3.0-cdh5.4.0-hadoop2.6.0-cdh5.4.0.jar/py4j/protocol.py",line
300, in get_return_valuepy4j.protocol.Py4JJavaError: An erroroccurred while
calling o44.collect.: org.apache.spark.SparkException: Jobaborted due to stage
failure: Task 0 in stage 1.0 failed 4 times, most recentfailure: Lost task 0.3
in stage 1.0 (TID 4,
stluhdpddev27.monsanto.com):org.apache.spark.api.python.PythonException:
Traceback (most recent call last): File
"/opt/cloudera/parcels/CDH-5.4.0-1.cdh5.4.0.p0.27/jars/spark-assembly-1.3.0-cdh5.4.0-hadoop2.6.0-cdh5.4.0.jar/pyspark/worker.py",line
101, in main process()
File"/opt/cloudera/parcels/CDH-5.4.0-1.cdh5.4.0.p0.27/jars/spark-assembly-1.3.0-cdh5.4.0-hadoop2.6.0-cdh5.4.0.jar/pyspark/worker.py",line
96, in process serializer.dump_stream(func(split_index, iterator), outfile)
File"/opt/cloudera/parcels/CDH-5.4.0-1.cdh5.4.0.p0.27/jars/spark-assembly-1.3.0-cdh5.4.0-hadoop2.6.0-cdh5.4.0.jar/pyspark/serializers.py",line
236, in dump_stream vs =list(itertools.islice(iterator, batch))
File"/opt/cloudera/parcels/CDH-5.4.0-1.cdh5.4.0.p0.27/jars/spark-assembly-1.3.0-cdh5.4.0-hadoop2.6.0-cdh5.4.0.jar/pyspark/rdd.py",line
1807, in <lambda> File"/usr/lib64/python2.6/json/__init__.py", line 307, in
loads return_default_decoder.decode(s)
File"/usr/lib64/python2.6/json/decoder.py", line 319, in decode obj, end
=self.raw_decode(s, idx=_w(s, 0).end()) File
"/usr/lib64/python2.6/json/decoder.py",line 338, in raw_decode
raiseValueError("No JSON object could be decoded")ValueError: No JSON object
could bedecoded at
org.apache.spark.api.python.PythonRDD$$anon$1.read(PythonRDD.scala:135)
at org.apache.spark.api.python.PythonRDD$$anon$1.<init>(PythonRDD.scala:176)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:94)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:277) at
org.apache.spark.rdd.RDD.iterator(RDD.scala:244) at
org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61) at
org.apache.spark.scheduler.Task.run(Task.scala:64) at
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:203) at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
atjava.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745) Driver stacktrace: at
org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1203)
atorg.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1192)
atorg.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1191)
atscala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at
org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1191)
atorg.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at
org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:693)
at scala.Option.foreach(Option.scala:236)
atorg.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:693)
at
org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1393)
atorg.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1354)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) Any
suggestions would be most welcome.
****************************************************************Below is the
code we’re running. We did add a few things tothe original example in our
attempts to get it working. from __future__ import print_function import
sysimport json from pyspark import SparkContextfrom pyspark.conf import
SparkConf import os.pathos.environ["SPARK_HOME"]
="/opt/cloudera/parcels/CDH-5.4.0-1.cdh5.4.0.p0.27/jars/"conf =
(SparkConf().setMaster('local').setAppName('a')) if __name__ == "__main__":
if len(sys.argv) != 3: print(""" Usage:hbase_inputformat <host>
<table> Run with example jar: ./bin/spark-submit--driver-class-path
/path/to/example/jar \ /path/to/examples/hbase_inputformat.py <host>
<table> [<znode>] Assumes you have somedata in HBase already, running on
<host>, in <table> optionally,you can specify parent znode for your
hbase cluster - <znode> """,file=sys.stderr) exit(-1) host =
sys.argv[1]table = sys.argv[2]sc = SparkContext(appName="HBaseInputFormat") #
Other options for configuring scan behavior are available.More information
available at#
https://github.com/apache/hbase/blob/master/hbase-server/src/main/java/org/apache/hadoop/hbase/mapreduce/TableInputFormat.javaconf
= {"hbase.zookeeper.quorum": host,"hbase.mapreduce.inputtable": table}if
len(sys.argv) > 3: conf ={"hbase.zookeeper.quorum": host,
"zookeeper.znode.parent":sys.argv[3], "hbase.mapreduce.inputtable":
table}keyConv
="org.apache.spark.examples.pythonconverters.ImmutableBytesWritableToStringConverter"valueConv
= "org.apache.spark.examples.pythonconverters.HBaseResultToStringConverter"
hbase_rdd = sc.newAPIHadoopRDD(
"org.apache.hadoop.hbase.mapreduce.TableInputFormat",
"org.apache.hadoop.hbase.io.ImmutableBytesWritable",
"org.apache.hadoop.hbase.client.Result", keyConverter=keyConv,
valueConverter=valueConv, conf=conf)hbase_rdd =
hbase_rdd.flatMapValues(lambda v:v.split("\n")).mapValues(json.loads)#
hbase_rdd = hbase_rdd.flatMapValues(lambda v:v.split("\n"))# hbase_rdd =
hbase_rdd.flatMapValues(lambda v:v.split("\n")).countByValue().items() output =
hbase_rdd.collect()# output = hbase_rddfor (k, v) in output: print((k, v))
sc.stop()
