Yi Yao created SPARK-5707:
-----------------------------
Summary: Enabling spark.sql.codegen throws ClassNotFound exception
Key: SPARK-5707
URL: https://issues.apache.org/jira/browse/SPARK-5707
Project: Spark
Issue Type: Bug
Components: SQL
Affects Versions: 1.2.0
Environment: yarn-client mode
Reporter: Yi Yao
org.apache.spark.SparkException: Job aborted due to stage failure: Task 13 in
stage 133.0 failed 4 times, most recent failure: Lost task 13.3 in stage 133.0
(TID 3066, cdh52-node2): java.io.IOException:
com.esotericsoftware.kryo.KryoException: Unable to find class:
__wrapper$1$81257352e1c844aebf09cb84fe9e7459.__wrapper$1$81257352e1c844aebf09cb84fe9e7459$SpecificRow$1
Serialization trace:
hashTable (org.apache.spark.sql.execution.joins.UniqueKeyHashedRelation)
at org.apache.spark.util.Utils$.tryOrIOException(Utils.scala:1011)
at
org.apache.spark.broadcast.TorrentBroadcast.readBroadcastBlock(TorrentBroadcast.scala:164)
at
org.apache.spark.broadcast.TorrentBroadcast._value$lzycompute(TorrentBroadcast.scala:64)
at
org.apache.spark.broadcast.TorrentBroadcast._value(TorrentBroadcast.scala:64)
at
org.apache.spark.broadcast.TorrentBroadcast.getValue(TorrentBroadcast.scala:87)
at org.apache.spark.broadcast.Broadcast.value(Broadcast.scala:70)
at
org.apache.spark.sql.execution.joins.BroadcastHashJoin$$anonfun$3.apply(BroadcastHashJoin.scala:62)
at
org.apache.spark.sql.execution.joins.BroadcastHashJoin$$anonfun$3.apply(BroadcastHashJoin.scala:61)
at org.apache.spark.rdd.RDD$$anonfun$13.apply(RDD.scala:601)
at org.apache.spark.rdd.RDD$$anonfun$13.apply(RDD.scala:601)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:230)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:230)
at org.apache.spark.rdd.MappedRDD.compute(MappedRDD.scala:31)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:230)
at org.apache.spark.rdd.CartesianRDD.compute(CartesianRDD.scala:75)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:230)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:230)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:230)
at org.apache.spark.rdd.MappedRDD.compute(MappedRDD.scala:31)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:230)
at org.apache.spark.rdd.CartesianRDD.compute(CartesianRDD.scala:75)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:230)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:230)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:230)
at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:263)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:230)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:61)
at org.apache.spark.scheduler.Task.run(Task.scala:56)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:196)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
SQL:
INSERT INTO TABLE ${hiveconf:TEMP_TABLE}
SELECT
s_store_name,
pr_review_date,
pr_review_content
FROM (
--select store_name for stores with flat or declining sales in 3 consecutive
months.
SELECT s_store_name
FROM store s
JOIN (
-- linear regression part
SELECT
temp.cat AS cat,
--SUM(temp.x)as sumX,
--SUM(temp.y)as sumY,
--SUM(temp.xy)as sumXY,
--SUM(temp.xx)as sumXSquared,
--count(temp.x) as N,
--N * sumXY - sumX * sumY AS numerator,
--N * sumXSquared - sumX*sumX AS denom
--numerator / denom as slope,
--(sumY - slope * sumX) / N as intercept
--(count(temp.x) * SUM(temp.xy) - SUM(temp.x) * SUM(temp.y)) AS numerator,
--(count(temp.x) * SUM(temp.xx) - SUM(temp.x) * SUM(temp.x)) AS denom
--numerator / denom as slope,
--(sumY - slope * sumX) / N as intercept
((count(temp.x) * SUM(temp.xy) - SUM(temp.x) * SUM(temp.y)) /
(count(temp.x) * SUM(temp.xx) - SUM(temp.x) * SUM(temp.x)) ) as slope,
(SUM(temp.y) - ((count(temp.x) * SUM(temp.xy) - SUM(temp.x) *
SUM(temp.y)) / (count(temp.x) * SUM(temp.xx) - SUM(temp.x) * SUM(temp.x)) ) *
SUM(temp.x)) / count(temp.x) as intercept
FROM (
SELECT
s.ss_store_sk AS cat,
s.ss_sold_date_sk AS x,
SUM(s.ss_net_paid) AS y,
s.ss_sold_date_sk * SUM(s.ss_net_paid) AS xy,
s.ss_sold_date_sk*s.ss_sold_date_sk AS xx
FROM store_sales s
--select date range
LEFT SEMI JOIN (
SELECT d_date_sk
FROM date_dim d
WHERE d.d_date >= '${hiveconf:q18_startDate}'
AND d.d_date <= '${hiveconf:q18_endDate}'
) dd ON ( s.ss_sold_date_sk=dd.d_date_sk )
WHERE s.ss_store_sk <= 18
GROUP BY s.ss_store_sk, s.ss_sold_date_sk
) temp
GROUP BY temp.cat
) c on s.s_store_sk = c.cat
WHERE c.slope < 0
) tmp
JOIN product_reviews pr on (true)
WHERE instr(pr.pr_review_content, tmp.s_store_name) > 0
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
