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https://issues.apache.org/jira/browse/SPARK-11330?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Saif Addin Ellafi updated SPARK-11330:
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    Summary: Filter operation on StringType after groupBy (2+ columns) brings 
no results when there are  (was: Filter operation on StringType after groupBy 
(2 columns) brings no results when there are)

> Filter operation on StringType after groupBy (2+ columns) brings no results 
> when there are
> ------------------------------------------------------------------------------------------
>
>                 Key: SPARK-11330
>                 URL: https://issues.apache.org/jira/browse/SPARK-11330
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 1.5.1
>         Environment: Stand alone Cluster of five servers (happens as well in 
> local mode). sqlContext instance of HiveContext (happens as well with 
> SQLContext)
> No special options other than driver memory and executor memory.
> Parquet partitions are 512 where there are 160 cores. Happens as well with 
> other partitioning
> Data is nearly 2 billion rows.
>            Reporter: Saif Addin Ellafi
>            Priority: Blocker
>
> val data = sqlContext.read.parquet("/var/data/Saif/ppnr_pqt")
> val res = data.groupBy("vintages", "yyyymm").count.persist()
> res.dtypes >>> res25: Array[(String, String)] = Array((vintages,StringType), 
> (yyyymm,IntegerType), (count,LongType))
> res.first >>> res24: org.apache.spark.sql.Row = [1967-06-01,200506,18750]
> val z = res.select("vintages", "yyyymm").filter("vintages = 
> '1967-06-01'").select("yyyymm").distinct.collect
> z.length >>> 0
> This does not happen if using another type of field, eg IntType
> val z = res.select("vintages", "yyyymm").filter("yyyymm = 
> 200506").select("yyyymm").distinct.collect
> z: Array[org.apache.spark.sql.Row] = Array([200506])
> Query to raw-data works fine:
> data.select("vintages").filter("vintages = '2007-01-01'").first >>> res4: 
> org.apache.spark.sql.Row = [2007-01-01]
> Originally, the issue happened with a larger aggregation operation, the 
> result was that data was inconsistent bringing different results every call.
> Reducing the operation step by step, I got into this issue.
> In any case, the original operation was:
> val data = sqlContext.read.parquet("/var/Saif/data_pqt")
> val res = data.groupBy("product", "band", "age", "vint", "mb", 
> "yyyymm").agg(count($"account_id").as("N"), 
> sum($"balance").as("balance_eom"), sum($"balancec").as("balance_eoc"), 
> sum($"spend").as("spend"), sum($"payment").as("payment"), 
> sum($"feoc").as("feoc"), sum($"cfintbal").as("cfintbal"), count($"newacct" 
> === 1).as("newacct")).persist()
> val z = res.select("vint", "yyyymm").filter("vint = 
> '2007-01-01'").select("yyyymm").distinct.collect
> z.length
> >>> res0: Int = 102
> res.unpersist()
> val z = res.select("vint", "yyyymm").filter("vint = 
> '2007-01-01'").select("yyyymm").distinct.collect
> z.length
> >>> res1: Int = 103



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