[jira] [Assigned] (HIVE-17225) HoS DPP pruning sink ops can target parallel work objects

2017-08-25 Thread Sahil Takiar (JIRA) 

 [ 
https://issues.apache.org/jira/browse/HIVE-17225?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Sahil Takiar reassigned HIVE-17225:
---

Assignee: Sahil Takiar  (was: Janaki Lahorani)

> HoS DPP pruning sink ops can target parallel work objects
> -
>
> Key: HIVE-17225
> URL: https://issues.apache.org/jira/browse/HIVE-17225
> Project: Hive
>  Issue Type: Sub-task
>  Components: Spark
>Affects Versions: 3.0.0
>Reporter: Sahil Takiar
>Assignee: Sahil Takiar
> Attachments: HIVE17225.1.patch
>
>
> Setup:
> {code:sql}
> SET hive.spark.dynamic.partition.pruning=true;
> SET hive.strict.checks.cartesian.product=false;
> SET hive.auto.convert.join=true;
> CREATE TABLE partitioned_table1 (col int) PARTITIONED BY (part_col int);
> CREATE TABLE regular_table1 (col int);
> CREATE TABLE regular_table2 (col int);
> ALTER TABLE partitioned_table1 ADD PARTITION (part_col = 1);
> ALTER TABLE partitioned_table1 ADD PARTITION (part_col = 2);
> ALTER TABLE partitioned_table1 ADD PARTITION (part_col = 3);
> INSERT INTO table regular_table1 VALUES (1), (2), (3), (4), (5), (6);
> INSERT INTO table regular_table2 VALUES (1), (2), (3), (4), (5), (6);
> INSERT INTO TABLE partitioned_table1 PARTITION (part_col = 1) VALUES (1);
> INSERT INTO TABLE partitioned_table1 PARTITION (part_col = 2) VALUES (2);
> INSERT INTO TABLE partitioned_table1 PARTITION (part_col = 3) VALUES (3);
> SELECT *
> FROM   partitioned_table1,
>regular_table1 rt1,
>regular_table2 rt2
> WHERE  rt1.col = partitioned_table1.part_col
>AND rt2.col = partitioned_table1.part_col;
> {code}
> Exception:
> {code}
> 2017-08-01T13:27:47,483 ERROR [b0d354a8-4cdb-4ba9-acec-27d14926aaf4 main] 
> ql.Driver: FAILED: Execution Error, return code 3 from 
> org.apache.hadoop.hive.ql.exec.spark.SparkTask. java.lang.RuntimeException: 
> org.apache.hadoop.hive.ql.metadata.HiveException: 
> java.io.FileNotFoundException: File 
> file:/Users/stakiar/Documents/idea/apache-hive/itests/qtest-spark/target/tmp/scratchdir/stakiar/b0d354a8-4cdb-4ba9-acec-27d14926aaf4/hive_2017-08-01_13-27-45_553_1088589686371686526-1/-mr-10004/3/5
>  does not exist
>   at 
> org.apache.hadoop.hive.ql.io.HiveInputFormat.init(HiveInputFormat.java:408)
>   at 
> org.apache.hadoop.hive.ql.io.CombineHiveInputFormat.getSplits(CombineHiveInputFormat.java:498)
>   at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:200)
>   at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
>   at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
>   at scala.Option.getOrElse(Option.scala:121)
>   at org.apache.spark.rdd.RDD.partitions(RDD.scala:246)
>   at 
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
>   at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
>   at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
>   at scala.Option.getOrElse(Option.scala:121)
>   at org.apache.spark.rdd.RDD.partitions(RDD.scala:246)
>   at org.apache.spark.rdd.UnionRDD$$anonfun$1.apply(UnionRDD.scala:82)
>   at org.apache.spark.rdd.UnionRDD$$anonfun$1.apply(UnionRDD.scala:82)
>   at 
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
>   at 
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
>   at scala.collection.immutable.List.foreach(List.scala:381)
>   at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
>   at scala.collection.immutable.List.map(List.scala:285)
>   at org.apache.spark.rdd.UnionRDD.getPartitions(UnionRDD.scala:82)
>   at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
>   at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
>   at scala.Option.getOrElse(Option.scala:121)
>   at org.apache.spark.rdd.RDD.partitions(RDD.scala:246)
>   at org.apache.spark.rdd.UnionRDD$$anonfun$1.apply(UnionRDD.scala:82)
>   at org.apache.spark.rdd.UnionRDD$$anonfun$1.apply(UnionRDD.scala:82)
>   at 
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
>   at 
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
>   at scala.collection.immutable.List.foreach(List.scala:381)
>   at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
>   at scala.collection.immutable.List.map(List.scala:285)
>   at org.apache.spark.rdd.UnionRDD.getPartitions(UnionRDD.scala:82)
>   at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
>   at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
>   at scala.Option.getOrElse(Option.scala:121)
>

[jira] [Assigned] (HIVE-17225) HoS DPP pruning sink ops can target parallel work objects

2017-08-02 Thread Janaki Lahorani (JIRA) 

 [ 
https://issues.apache.org/jira/browse/HIVE-17225?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Janaki Lahorani reassigned HIVE-17225:
--

Assignee: Janaki Lahorani  (was: Sahil Takiar)

> HoS DPP pruning sink ops can target parallel work objects
> -
>
> Key: HIVE-17225
> URL: https://issues.apache.org/jira/browse/HIVE-17225
> Project: Hive
>  Issue Type: Sub-task
>  Components: Spark
>Affects Versions: 3.0.0
>Reporter: Sahil Takiar
>Assignee: Janaki Lahorani
>
> Setup:
> {code:sql}
> SET hive.spark.dynamic.partition.pruning=true;
> SET hive.strict.checks.cartesian.product=false;
> SET hive.auto.convert.join=true;
> CREATE TABLE partitioned_table1 (col int) PARTITIONED BY (part_col int);
> CREATE TABLE regular_table1 (col int);
> CREATE TABLE regular_table2 (col int);
> ALTER TABLE partitioned_table1 ADD PARTITION (part_col = 1);
> ALTER TABLE partitioned_table1 ADD PARTITION (part_col = 2);
> ALTER TABLE partitioned_table1 ADD PARTITION (part_col = 3);
> INSERT INTO table regular_table1 VALUES (1), (2), (3), (4), (5), (6);
> INSERT INTO table regular_table2 VALUES (1), (2), (3), (4), (5), (6);
> INSERT INTO TABLE partitioned_table1 PARTITION (part_col = 1) VALUES (1);
> INSERT INTO TABLE partitioned_table1 PARTITION (part_col = 2) VALUES (2);
> INSERT INTO TABLE partitioned_table1 PARTITION (part_col = 3) VALUES (3);
> SELECT *
> FROM   partitioned_table1,
>regular_table1 rt1,
>regular_table2 rt2
> WHERE  rt1.col = partitioned_table1.part_col
>AND rt2.col = partitioned_table1.part_col;
> {code}
> Exception:
> {code}
> 2017-08-01T13:27:47,483 ERROR [b0d354a8-4cdb-4ba9-acec-27d14926aaf4 main] 
> ql.Driver: FAILED: Execution Error, return code 3 from 
> org.apache.hadoop.hive.ql.exec.spark.SparkTask. java.lang.RuntimeException: 
> org.apache.hadoop.hive.ql.metadata.HiveException: 
> java.io.FileNotFoundException: File 
> file:/Users/stakiar/Documents/idea/apache-hive/itests/qtest-spark/target/tmp/scratchdir/stakiar/b0d354a8-4cdb-4ba9-acec-27d14926aaf4/hive_2017-08-01_13-27-45_553_1088589686371686526-1/-mr-10004/3/5
>  does not exist
>   at 
> org.apache.hadoop.hive.ql.io.HiveInputFormat.init(HiveInputFormat.java:408)
>   at 
> org.apache.hadoop.hive.ql.io.CombineHiveInputFormat.getSplits(CombineHiveInputFormat.java:498)
>   at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:200)
>   at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
>   at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
>   at scala.Option.getOrElse(Option.scala:121)
>   at org.apache.spark.rdd.RDD.partitions(RDD.scala:246)
>   at 
> org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
>   at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
>   at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
>   at scala.Option.getOrElse(Option.scala:121)
>   at org.apache.spark.rdd.RDD.partitions(RDD.scala:246)
>   at org.apache.spark.rdd.UnionRDD$$anonfun$1.apply(UnionRDD.scala:82)
>   at org.apache.spark.rdd.UnionRDD$$anonfun$1.apply(UnionRDD.scala:82)
>   at 
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
>   at 
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
>   at scala.collection.immutable.List.foreach(List.scala:381)
>   at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
>   at scala.collection.immutable.List.map(List.scala:285)
>   at org.apache.spark.rdd.UnionRDD.getPartitions(UnionRDD.scala:82)
>   at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
>   at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
>   at scala.Option.getOrElse(Option.scala:121)
>   at org.apache.spark.rdd.RDD.partitions(RDD.scala:246)
>   at org.apache.spark.rdd.UnionRDD$$anonfun$1.apply(UnionRDD.scala:82)
>   at org.apache.spark.rdd.UnionRDD$$anonfun$1.apply(UnionRDD.scala:82)
>   at 
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
>   at 
> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
>   at scala.collection.immutable.List.foreach(List.scala:381)
>   at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
>   at scala.collection.immutable.List.map(List.scala:285)
>   at org.apache.spark.rdd.UnionRDD.getPartitions(UnionRDD.scala:82)
>   at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:248)
>   at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:246)
>   at scala.Option.getOrElse(Option.scala:121)
>   at