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https://issues.apache.org/jira/browse/SPARK-32809?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17191475#comment-17191475
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Hyukjin Kwon commented on SPARK-32809:
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Please also fix the title.
What's the expected results and actual results?
Also, Spark 2.2 is EOL which doesn't have maintenence releases anymore. It
would be great if it can be still reproduced in Spark 2.4+.
> RDD分区数对于计算结果的影响
> ---------------
>
> Key: SPARK-32809
> URL: https://issues.apache.org/jira/browse/SPARK-32809
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.2.0
> Reporter: zhangchenglong
> Priority: Major
>
> class Exec3 {
> private val exec: SparkConf = new
> SparkConf().setMaster("local[1]").setAppName("exec3")
> private val context = new SparkContext(exec)
> context.setCheckpointDir("checkPoint")
>
> /**
> * get total number by key
> * in this project desired results are ("apple",25) ("huwei"，20)
> * but in fact i get ("apple",150) ("huawei"，20)
> * when i change it to local[3] the result is correct
> * i want to know which cause it and how to slove it
> */
> @Test
> def testError(): Unit ={
> val rdd = context.parallelize(Seq(("apple", 10), ("apple", 15), ("huawei",
> 20)))
> rdd.aggregateByKey(1.0)(
> seqOp = (zero, price) => price * zero,
> combOp = (curr, agg) => curr + agg
> ).collect().foreach(println(_))
> context.stop()
> }
> }
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