I tried the following
1)
./bin/spark-submit -v --master yarn-cluster --driver-class-path
/home/dvasthimal/spark1.3/mysql-connector-java-5.1.34.jar:/apache/hadoop/share/hadoop/common/hadoop-common-2.4.1-EBAY-2.jar:/apache/hadoop/lib/hadoop-lzo-0.6.0.jar:/apache/hadoop-2.4.1-2.1.3.0-2-EBAY/share/hadoop/yarn/lib/guava-11.0.2.jar:
*$SPARK_HOME/conf/hive-site.xml* --jars
/home/dvasthimal/spark1.3/spark-avro_2.10-1.0.0.jar,/home/dvasthimal/spark1.3/spark-1.3.0-bin-hadoop2.4/lib/datanucleus-api-jdo-3.2.6.jar,/home/dvasthimal/spark1.3/spark-1.3.0-bin-hadoop2.4/lib/datanucleus-core-3.2.10.jar,/home/dvasthimal/spark1.3/spark-1.3.0-bin-hadoop2.4/lib/datanucleus-rdbms-3.2.9.jar
--num-executors 1 --driver-memory 4g --driver-java-options
"-XX:MaxPermSize=2G" --executor-memory 2g --executor-cores 1 --queue
hdmi-express --class com.ebay.ep.poc.spark.reporting.SparkApp
spark_reporting-1.0-SNAPSHOT.jar startDate=2015-02-16 endDate=2015-02-16
input=/user/dvasthimal/epdatasets/successdetail1/part-r-00000.avro
subcommand=successevents2 output=/user/dvasthimal/epdatasets/successdetail2
This throws dw_bid not found. Looks like Spark SQL is unable to read my
existing Hive metastore and creates its own and hence complains that table
is not found.
2)
./bin/spark-submit -v --master yarn-cluster --driver-class-path
/home/dvasthimal/spark1.3/mysql-connector-java-5.1.34.jar:/apache/hadoop/share/hadoop/common/hadoop-common-2.4.1-EBAY-2.jar:/apache/hadoop/lib/hadoop-lzo-0.6.0.jar:/apache/hadoop-2.4.1-2.1.3.0-2-EBAY/share/hadoop/yarn/lib/guava-11.0.2.jar
--jars
/home/dvasthimal/spark1.3/spark-avro_2.10-1.0.0.jar,/home/dvasthimal/spark1.3/spark-1.3.0-bin-hadoop2.4/lib/datanucleus-api-jdo-3.2.6.jar,/home/dvasthimal/spark1.3/spark-1.3.0-bin-hadoop2.4/lib/datanucleus-core-3.2.10.jar,/home/dvasthimal/spark1.3/spark-1.3.0-bin-hadoop2.4/lib/datanucleus-rdbms-3.2.9.jar:
*$SPARK_HOME/conf/hive-site.xml* --num-executors 1 --driver-memory 4g
--driver-java-options "-XX:MaxPermSize=2G" --executor-memory 2g
--executor-cores 1 --queue hdmi-express --class
com.ebay.ep.poc.spark.reporting.SparkApp spark_reporting-1.0-SNAPSHOT.jar
startDate=2015-02-16 endDate=2015-02-16
input=/user/dvasthimal/epdatasets/successdetail1/part-r-00000.avro
subcommand=successevents2 output=/user/dvasthimal/epdatasets/successdetail2
This time i do not get above error, however i get MySQL driver not found
exception. Looks like this is even before its able to communicate to Hive.
Caused by: org.datanucleus.exceptions.NucleusException: Attempt to invoke
the "BONECP" plugin to create a ConnectionPool gave an error : The
specified datastore driver ("com.mysql.jdbc.Driver") was not found in the
CLASSPATH. Please check your CLASSPATH specification, and the name of the
driver.
In both above cases, i do have hive-site.xml in Spark/conf folder.
3)
./bin/spark-submit -v --master yarn-cluster --driver-class-path
/home/dvasthimal/spark1.3/mysql-connector-java-5.1.34.jar:/apache/hadoop/share/hadoop/common/hadoop-common-2.4.1-EBAY-2.jar:/apache/hadoop/lib/hadoop-lzo-0.6.0.jar:/apache/hadoop-2.4.1-2.1.3.0-2-EBAY/share/hadoop/yarn/lib/guava-11.0.2.jar
--jars
/home/dvasthimal/spark1.3/spark-avro_2.10-1.0.0.jar,/home/dvasthimal/spark1.3/spark-1.3.0-bin-hadoop2.4/lib/datanucleus-api-jdo-3.2.6.jar,/home/dvasthimal/spark1.3/spark-1.3.0-bin-hadoop2.4/lib/datanucleus-core-3.2.10.jar,/home/dvasthimal/spark1.3/spark-1.3.0-bin-hadoop2.4/lib/datanucleus-rdbms-3.2.9.jar--num-executors
1 --driver-memory 4g --driver-java-options "-XX:MaxPermSize=2G"
--executor-memory 2g --executor-cores 1 --queue hdmi-express --class
com.ebay.ep.poc.spark.reporting.SparkApp spark_reporting-1.0-SNAPSHOT.jar
startDate=2015-02-16 endDate=2015-02-16
input=/user/dvasthimal/epdatasets/successdetail1/part-r-00000.avro
subcommand=successevents2 output=/user/dvasthimal/epdatasets/successdetail2
I do not specify hive-site.xml in --jars or --driver-class-path. Its
present in spark/conf folder as per
https://spark.apache.org/docs/1.3.0/sql-programming-guide.html#hive-tables.
In this case i get same error as #1. dw_bid table not found.
I want Spark SQL to know that there are tables in Hive and read that data.
As per guide it looks like Spark SQL has that support.
Please suggest.
Regards,
Deepak
On Thu, Mar 26, 2015 at 9:01 PM, ÐΞ€ρ@Ҝ (๏̯͡๏) <deepuj...@gmail.com> wrote:
> Stack Trace:
>
> 15/03/26 08:25:42 INFO ql.Driver: OK
> 15/03/26 08:25:42 INFO log.PerfLogger: <PERFLOG method=releaseLocks
> from=org.apache.hadoop.hive.ql.Driver>
> 15/03/26 08:25:42 INFO log.PerfLogger: </PERFLOG method=releaseLocks
> start=1427383542966 end=1427383542966 duration=0
> from=org.apache.hadoop.hive.ql.Driver>
> 15/03/26 08:25:42 INFO log.PerfLogger: </PERFLOG method=Driver.run
> start=1427383535203 end=1427383542966 duration=7763
> from=org.apache.hadoop.hive.ql.Driver>
> 15/03/26 08:25:42 INFO metastore.HiveMetaStore: 0: get_tables: db=default
> pat=.*
> 15/03/26 08:25:42 INFO HiveMetaStore.audit: ugi=dvasthimal
> ip=unknown-ip-addr cmd=get_tables: db=default pat=.*
> 15/03/26 08:25:43 INFO parse.ParseDriver: Parsing command: insert
> overwrite table sojsuccessevents2_spark select
> guid,sessionKey,sessionStartDate,sojDataDate,seqNum,eventTimestamp,siteId,successEventType,sourceType,itemId,
> shopCartId,b.transaction_Id as transactionId,offerId,b.bdr_id as
> userId,priorPage1SeqNum,priorPage1PageId,exclWMSearchAttemptSeqNum,exclPriorSearchPageId,
> exclPriorSearchSeqNum,exclPriorSearchCategory,exclPriorSearchL1,exclPriorSearchL2,currentImpressionId,sourceImpressionId,exclPriorSearchSqr,exclPriorSearchSort,
> isDuplicate,b.bid_date as
> transactionDate,auctionTypeCode,isBin,leafCategoryId,itemSiteId,b.qty_bid
> as bidQuantity, b.bid_amt_unit_lstg_curncy * b.bid_exchng_rate as
>
> bidAmtUsd,offerQuantity,offerAmountUsd,offerCreateDate,buyerSegment,buyerCountryId,sellerId,sellerCountryId,
> sellerStdLevel,cssSellerLevel,a.experimentChannel from sojsuccessevents1 a
> join dw_bid b on a.itemId = b.item_id and a.transactionId =
> b.transaction_id where b.auct_end_dt >= '2015-02-16' AND b.bid_dt >=
> '2015-02-16' AND b.bid_type_code IN (1,9) AND b.bdr_id > 0 AND (
> b.bid_flags & 32) = 0 and lower(a.successEventType) IN ('bid','bin')
> 15/03/26 08:25:43 INFO parse.ParseDriver: Parse Completed
> 15/03/26 08:25:43 INFO metastore.HiveMetaStore: 0: get_table : db=default
> tbl=sojsuccessevents2_spark
> 15/03/26 08:25:43 INFO HiveMetaStore.audit: ugi=dvasthimal
> ip=unknown-ip-addr cmd=get_table : db=default tbl=sojsuccessevents2_spark
> 15/03/26 08:25:44 INFO metastore.HiveMetaStore: 0: get_table : db=default
> tbl=dw_bid
> 15/03/26 08:25:44 INFO HiveMetaStore.audit: ugi=dvasthimal
> ip=unknown-ip-addr cmd=get_table : db=default tbl=dw_bid
> 15/03/26 08:25:44 ERROR metadata.Hive:
> NoSuchObjectException(message:default.dw_bid table not found)
> at
> org.apache.hadoop.hive.metastore.HiveMetaStore$HMSHandler.get_table(HiveMetaStore.java:1560)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:606)
> at
> org.apache.hadoop.hive.metastore.RetryingHMSHandler.invoke(RetryingHMSHandler.java:105)
> at com.sun.proxy.$Proxy31.get_table(Unknown Source)
> at
> org.apache.hadoop.hive.metastore.HiveMetaStoreClient.getTable(HiveMetaStoreClient.java:997)
> 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.hadoop.hive.metastore.RetryingMetaStoreClient.invoke(RetryingMetaStoreClient.java:89)
> at com.sun.proxy.$Proxy32.getTable(Unknown Source)
> at org.apache.hadoop.hive.ql.metadata.Hive.getTable(Hive.java:976)
> at org.apache.hadoop.hive.ql.metadata.Hive.getTable(Hive.java:950)
> at
> org.apache.spark.sql.hive.HiveMetastoreCatalog.lookupRelation(HiveMetastoreCatalog.scala:180)
> at org.apache.spark.sql.hive.HiveContext$$anon$1.org
> $apache$spark$sql$catalyst$analysis$OverrideCatalog$$super$lookupRelation(HiveContext.scala:252)
> at
> org.apache.spark.sql.catalyst.analysis.OverrideCatalog$$anonfun$lookupRelation$3.apply(Catalog.scala:161)
> at
> org.apache.spark.sql.catalyst.analysis.OverrideCatalog$$anonfun$lookupRelation$3.apply(Catalog.scala:161)
> at scala.Option.getOrElse(Option.scala:120)
> at
> org.apache.spark.sql.catalyst.analysis.OverrideCatalog$class.lookupRelation(Catalog.scala:161)
> at
> org.apache.spark.sql.hive.HiveContext$$anon$1.lookupRelation(HiveContext.scala:252)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.getTable(Analyzer.scala:175)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$$anonfun$apply$6.applyOrElse(Analyzer.scala:187)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$$anonfun$apply$6.applyOrElse(Analyzer.scala:182)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:187)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:187)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:50)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:186)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:207)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
> at scala.collection.AbstractIterator.to(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformChildrenDown(TreeNode.scala:236)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:192)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:207)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
> at scala.collection.AbstractIterator.to(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformChildrenDown(TreeNode.scala:236)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:192)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:207)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
> at scala.collection.AbstractIterator.to(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformChildrenDown(TreeNode.scala:236)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:192)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:207)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
> at scala.collection.AbstractIterator.to(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformChildrenDown(TreeNode.scala:236)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:194)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:177)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.apply(Analyzer.scala:182)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.apply(Analyzer.scala:172)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(RuleExecutor.scala:61)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(RuleExecutor.scala:59)
> at
> scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:111)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1.apply(RuleExecutor.scala:59)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1.apply(RuleExecutor.scala:51)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.apply(RuleExecutor.scala:51)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.analyzed$lzycompute(SQLContext.scala:1071)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.analyzed(SQLContext.scala:1071)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.assertAnalyzed(SQLContext.scala:1069)
> at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:133)
> at org.apache.spark.sql.DataFrame$.apply(DataFrame.scala:51)
> at org.apache.spark.sql.hive.HiveContext.sql(HiveContext.scala:92)
> at
> com.ebay.ep.poc.spark.reporting.process.service.HadoopSuccessEvents2Service.execute(HadoopSuccessEvents2Service.scala:32)
> at com.ebay.ep.poc.spark.reporting.SparkApp$.main(SparkApp.scala:30)
> at com.ebay.ep.poc.spark.reporting.SparkApp.main(SparkApp.scala)
> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
> at
> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
> at
> sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
> at java.lang.reflect.Method.invoke(Method.java:606)
> at
> org.apache.spark.deploy.yarn.ApplicationMaster$$anon$2.run(ApplicationMaster.scala:480)
>
> 15/03/26 08:25:44 ERROR yarn.ApplicationMaster: User class threw
> exception: no such table List(dw_bid); line 1 pos 843
> org.apache.spark.sql.AnalysisException: no such table List(dw_bid); line 1
> pos 843
> at
> org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.getTable(Analyzer.scala:178)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$$anonfun$apply$6.applyOrElse(Analyzer.scala:187)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$$anonfun$apply$6.applyOrElse(Analyzer.scala:182)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:187)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:187)
> at
> org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:50)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:186)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:207)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
> at scala.collection.AbstractIterator.to(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformChildrenDown(TreeNode.scala:236)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:192)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:207)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
> at scala.collection.AbstractIterator.to(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformChildrenDown(TreeNode.scala:236)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:192)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:207)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
> at scala.collection.AbstractIterator.to(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformChildrenDown(TreeNode.scala:236)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:192)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$4.apply(TreeNode.scala:207)
> at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
> at scala.collection.Iterator$class.foreach(Iterator.scala:727)
> at scala.collection.AbstractIterator.foreach(Iterator.scala:1157)
> at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:48)
> at
> scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:103)
> at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:47)
> at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:273)
> at scala.collection.AbstractIterator.to(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:265)
> at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1157)
> at
> scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:252)
> at scala.collection.AbstractIterator.toArray(Iterator.scala:1157)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformChildrenDown(TreeNode.scala:236)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:194)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:177)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.apply(Analyzer.scala:182)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.apply(Analyzer.scala:172)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(RuleExecutor.scala:61)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(RuleExecutor.scala:59)
> at
> scala.collection.LinearSeqOptimized$class.foldLeft(LinearSeqOptimized.scala:111)
> at scala.collection.immutable.List.foldLeft(List.scala:84)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1.apply(RuleExecutor.scala:59)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1.apply(RuleExecutor.scala:51)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.apply(RuleExecutor.scala:51)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.analyzed$lzycompute(SQLContext.scala:1071)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.analyzed(SQLContext.scala:1071)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.assertAnalyzed(SQLContext.scala:1069)
> at org.apache.spark.sql.DataFrame.<init>(DataFrame.scala:133)
> at org.apache.spark.sql.DataFrame$.apply(DataFrame.scala:51)
> at org.apache.spark.sql.hive.HiveContext.sql(HiveContext.scala:92)
> at
> com.ebay.ep.poc.spark.reporting.process.service.HadoopSuccessEvents2Service.execute(HadoopSuccessEvents2Service.scala:32)
> at com.ebay.ep.poc.spark.reporting.SparkApp$.main(SparkApp.scala:30)
> at com.ebay.ep.poc.spark.reporting.SparkApp.main(SparkApp.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.yarn.ApplicationMaster$$anon$2.run(ApplicationMaster.scala:480)
> 15/03/26 08:25:44 INFO yarn.ApplicationMaster: Final app status: FAILED,
> exitCode: 15, (reason: User class threw exception: no such table
> List(dw_bid); line 1 pos 843)
> 15/03/26 08:25:44 INFO yarn.ApplicationMaster: Invoking sc stop from
> shutdown hook
>
>
> On Thu, Mar 26, 2015 at 8:58 PM, ÐΞ€ρ@Ҝ (๏̯͡๏) <deepuj...@gmail.com>
> wrote:
>
>> Hello Michael,
>> Thanks for your time.
>>
>> 1. show tables from Spark program returns nothing.
>> 2. What entities are you talking about ? (I am actually new to Hive as
>> well)
>>
>>
>> On Thu, Mar 26, 2015 at 8:35 PM, Michael Armbrust <mich...@databricks.com
>> > wrote:
>>
>>> What does "show tables" return? You can also run "SET <optionName>" to
>>> make sure that entries from you hive site are being read correctly.
>>>
>>> On Thu, Mar 26, 2015 at 4:02 AM, ÐΞ€ρ@Ҝ (๏̯͡๏) <deepuj...@gmail.com>
>>> wrote:
>>>
>>>> I have tables dw_bid that is created in Hive and has nothing to do with
>>>> Spark. I have data in avro that i want to join with dw_bid table, this
>>>> join needs to be done using Spark SQL. However for some reason Spark says
>>>> dw_bid table does not exist. How do i say spark that dw_bid is a table
>>>> created in Hive and read it.
>>>>
>>>>
>>>> Query that is run from Spark SQL
>>>> ==============================
>>>> insert overwrite table sojsuccessevents2_spark select
>>>> guid,sessionKey,sessionStartDate,sojDataDate,seqNum,eventTimestamp,siteId,successEventType,sourceType,itemId,
>>>> shopCartId,b.transaction_Id as transactionId,offerId,b.bdr_id as
>>>> userId,priorPage1SeqNum,priorPage1PageId,exclWMSearchAttemptSeqNum,exclPriorSearchPageId,
>>>> exclPriorSearchSeqNum,exclPriorSearchCategory,exclPriorSearchL1,exclPriorSearchL2,currentImpressionId,sourceImpressionId,exclPriorSearchSqr,exclPriorSearchSort,
>>>> isDuplicate,b.bid_date as
>>>> transactionDate,auctionTypeCode,isBin,leafCategoryId,itemSiteId,b.qty_bid
>>>> as bidQuantity, b.bid_amt_unit_lstg_curncy * b.bid_exchng_rate as
>>>>
>>>> bidAmtUsd,offerQuantity,offerAmountUsd,offerCreateDate,buyerSegment,buyerCountryId,sellerId,sellerCountryId,
>>>> sellerStdLevel,cssSellerLevel,a.experimentChannel from sojsuccessevents1 a
>>>> join dw_bid b on a.itemId = b.item_id and a.transactionId =
>>>> b.transaction_id where b.auct_end_dt >= '2015-02-16' AND b.bid_dt >=
>>>> '2015-02-16' AND b.bid_type_code IN (1,9) AND b.bdr_id > 0 AND (
>>>> b.bid_flags & 32) = 0 and lower(a.successEventType) IN ('bid','bin')
>>>>
>>>>
>>>> If i create sojsuccessevents2_spark from hive command line and run
>>>> above command form Spark SQL program then i get error
>>>> "sojsuccessevents2_spark table not found".
>>>>
>>>> Hence i dropped the command from Hive and run create table
>>>> sojsuccessevents2_spark from Spark SQL before running above command and it
>>>> works until it hits next road block "dw_bid table not found"
>>>>
>>>> This makes me belive that Spark for some reason is not able to
>>>> read/understand the tables created outside Spark. I did copy
>>>> /apache/hive/conf/hive-site.xml into Spark conf directory.
>>>>
>>>> Please suggest.
>>>>
>>>>
>>>> Logs
>>>> ———
>>>> 15/03/26 03:50:40 INFO HiveMetaStore.audit: ugi=dvasthimal
>>>> ip=unknown-ip-addr cmd=get_table : db=default tbl=dw_bid
>>>> 15/03/26 03:50:40 ERROR metadata.Hive:
>>>> NoSuchObjectException(message:default.dw_bid table not found)
>>>> at
>>>> org.apache.hadoop.hive.metastore.HiveMetaStore$HMSHandler.get_table(HiveMetaStore.java:1560)
>>>>
>>>>
>>>>
>>>> 15/03/26 03:50:40 ERROR yarn.ApplicationMaster: User class threw
>>>> exception: no such table List(dw_bid); line 1 pos 843
>>>> org.apache.spark.sql.AnalysisException: no such table List(dw_bid);
>>>> line 1 pos 843
>>>> at
>>>> org.apache.spark.sql.catalyst.analysis.package$AnalysisErrorAt.failAnalysis(package.scala:42)
>>>> at
>>>> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$.getTable(Analyzer.scala:178)
>>>> at
>>>> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveRelations$$anonfun$apply$6.applyOrElse(Analyzer.scala:187)
>>>>
>>>>
>>>>
>>>> Regards,
>>>> Deepak
>>>>
>>>>
>>>> On Thu, Mar 26, 2015 at 4:27 PM, ÐΞ€ρ@Ҝ (๏̯͡๏) <deepuj...@gmail.com>
>>>> wrote:
>>>>
>>>>> I have this query
>>>>>
>>>>> insert overwrite table sojsuccessevents2_spark select
>>>>> guid,sessionKey,sessionStartDate,sojDataDate,seqNum,eventTimestamp,siteId,successEventType,sourceType,itemId,
>>>>> shopCartId,b.transaction_Id as transactionId,offerId,b.bdr_id as
>>>>> userId,priorPage1SeqNum,priorPage1PageId,exclWMSearchAttemptSeqNum,exclPriorSearchPageId,
>>>>> exclPriorSearchSeqNum,exclPriorSearchCategory,exclPriorSearchL1,exclPriorSearchL2,currentImpressionId,sourceImpressionId,exclPriorSearchSqr,exclPriorSearchSort,
>>>>> isDuplicate,b.bid_date as
>>>>> transactionDate,auctionTypeCode,isBin,leafCategoryId,itemSiteId,b.qty_bid
>>>>> as bidQuantity, b.bid_amt_unit_lstg_curncy * b.bid_exchng_rate as
>>>>>
>>>>> bidAmtUsd,offerQuantity,offerAmountUsd,offerCreateDate,buyerSegment,buyerCountryId,sellerId,sellerCountryId,
>>>>> sellerStdLevel,cssSellerLevel,a.experimentChannel from sojsuccessevents1
>>>>> a *join
>>>>> dw_bid b* on a.itemId = b.item_id and a.transactionId =
>>>>> b.transaction_id where b.auct_end_dt >= '2015-02-16' AND b.bid_dt >=
>>>>> '2015-02-16' AND b.bid_type_code IN (1,9) AND b.bdr_id > 0 AND (
>>>>> b.bid_flags & 32) = 0 and lower(a.successEventType) IN ('bid','bin')
>>>>>
>>>>>
>>>>> If i create sojsuccessevents2_spark from hive command line and run
>>>>> above command form Spark SQL program then i get error
>>>>> "sojsuccessevents2_spark table not found".
>>>>>
>>>>> Hence i dropped the command from Hive and run create table
>>>>> sojsuccessevents2_spark from Spark SQL before running above command and it
>>>>> works until it hits next road block "*dw_bid table not found"*
>>>>>
>>>>> This makes me belive that Spark for some reason is not able to
>>>>> read/understand the tables created outside Spark. I did copy
>>>>> /apache/hive/conf/hive-site.xml into Spark conf directory.
>>>>>
>>>>> Please suggest.
>>>>>
>>>>> Regards,
>>>>> Deepak
>>>>>
>>>>>
>>>>> On Thu, Mar 26, 2015 at 1:26 PM, ÐΞ€ρ@Ҝ (๏̯͡๏) <deepuj...@gmail.com>
>>>>> wrote:
>>>>>
>>>>>> I have a hive table named dw_bid, when i run hive from command prompt
>>>>>> and run describe dw_bid, it works.
>>>>>>
>>>>>> I want to join a avro file (table) in HDFS with this hive dw_bid
>>>>>> table and i refer it as dw_bid from Spark SQL program, however i see
>>>>>>
>>>>>> 15/03/26 00:31:01 INFO HiveMetaStore.audit: ugi=dvasthimal
>>>>>> ip=unknown-ip-addr cmd=get_table : db=default tbl=dw_bid
>>>>>> 15/03/26 00:31:01 ERROR metadata.Hive:
>>>>>> NoSuchObjectException(message:default.dw_bid table not found)
>>>>>> at
>>>>>> org.apache.hadoop.hive.metastore.HiveMetaStore$HMSHandler.get_table(HiveMetaStore.java:1560)
>>>>>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
>>>>>> at
>>>>>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
>>>>>>
>>>>>>
>>>>>> Code:
>>>>>>
>>>>>> val successDetail_S1 = sqlContext.avroFile(input)
>>>>>> successDetail_S1.registerTempTable("sojsuccessevents1")
>>>>>> val countS1 = sqlContext.sql("select
>>>>>> guid,sessionKey,sessionStartDate,sojDataDate,seqNum,eventTimestamp,siteId,successEventType,sourceType,itemId,"
>>>>>> +
>>>>>> " shopCartId,b.transaction_Id as
>>>>>> transactionId,offerId,b.bdr_id as
>>>>>> userId,priorPage1SeqNum,priorPage1PageId,exclWMSearchAttemptSeqNum,exclPriorSearchPageId,"
>>>>>> +
>>>>>> "
>>>>>> exclPriorSearchSeqNum,exclPriorSearchCategory,exclPriorSearchL1,exclPriorSearchL2,currentImpressionId,sourceImpressionId,exclPriorSearchSqr,exclPriorSearchSort,"
>>>>>> +
>>>>>> " isDuplicate,b.bid_date as
>>>>>> transactionDate,auctionTypeCode,isBin,leafCategoryId,itemSiteId,b.qty_bid
>>>>>> as bidQuantity," +
>>>>>> " b.bid_amt_unit_lstg_curncy * b.bid_exchng_rate as
>>>>>>
>>>>>> bidAmtUsd,offerQuantity,offerAmountUsd,offerCreateDate,buyerSegment,buyerCountryId,sellerId,sellerCountryId,"
>>>>>> +
>>>>>> " sellerStdLevel,cssSellerLevel,a.experimentChannel" +
>>>>>> " from sojsuccessevents1 a join dw_bid b " +
>>>>>> " on a.itemId = b.item_id and a.transactionId =
>>>>>> b.transaction_id " +
>>>>>> " where b.bid_type_code IN (1,9) AND b.bdr_id > 0 AND (
>>>>>> b.bid_flags & 32) = 0 and lower(a.successEventType) IN ('bid','bin')")
>>>>>> println("countS1.first:" + countS1.first)
>>>>>>
>>>>>>
>>>>>>
>>>>>> Any suggestions on how to refer a hive table form Spark SQL?
>>>>>> --
>>>>>>
>>>>>> Deepak
>>>>>>
>>>>>>
>>>>>
>>>>>
>>>>> --
>>>>> Deepak
>>>>>
>>>>>
>>>>
>>>>
>>>> --
>>>> Deepak
>>>>
>>>>
>>>
>>
>>
>> --
>> Deepak
>>
>>
>
>
> --
> Deepak
>
>
--
Deepak
