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https://issues.apache.org/jira/browse/SPARK-12030?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Maciej Bryński updated SPARK-12030:
-----------------------------------
Description:
I have following issue.
I created 2 dataframes from JDBC (MySQL) and joined them (t1 has fk1 to t2)
{code}
t1 = sqlCtx.read.jdbc("jdbc:mysql://XXX", t1, id1, 0, size1, 200).cache()
t2 = sqlCtx.read.jdbc("jdbc:mysql://XXX", t2, id2, 0, size1, 200).cache()
joined = t1.join(t2, t1.fk1 == t2.id2, "left_outer")
{code}
Important: both table are cached, so results should be the same on every query.
Then I did come counts:
{code}
t1.count() -> 5900729
t1.registerTempTable("t1")
sqlCtx.sql("select distinct(id1) from t1").count() -> 5900729
t2.count() -> 54298
joined.count() -> 5900729
{code}
And here magic begins - I counted distinct id1 from joined table
{code}
joined.registerTempTable("joined")
sqlCtx.sql("select distinct(id1) from joined").count()
{code}
Results varies *(are different on every run)* between 5899000 and
5900000 but never are equal to 5900729.
In addition. I did more queries:
{code}
sqlCtx.sql("select id1, count(*) from joined group by id1 having count(*) >
1").collect()
{code}
This gives some results but this query return *1*
{code}
len(sqlCtx.sql("select * from joined where id1 = result").collect())
{code}
What's wrong ?
was:
I have following issue.
I created 2 dataframes from JDBC (MySQL) and joined them (t1 has fk1 to t2)
{code}
t1 = sqlCtx.read.jdbc("jdbc:mysql://XXX", t1, id1, 0, size1, 200).cache()
t2 = sqlCtx.read.jdbc("jdbc:mysql://XXX", t2, id2, 0, size1, 200).cache()
joined = t1.join(t2, t1.fk1 == t2.id2, "left_outer")
{code}
Important: both table are cached
Then I did come counts:
{code}
t1.count() -> 5900729
t1.registerTempTable("t1")
sqlCtx.sql("select distinct(id1) from t1").count() -> 5900729
t2.count() -> 54298
joined.count() -> 5900729
{code}
And here magic begins - I counted distinct id1 from joined table
{code}
joined.registerTempTable("joined")
sqlCtx.sql("select distinct(id1) from joined").count()
{code}
Results varies *(are different on every run)* between 5899000 and
5900000 but never are equal to 5900729.
In addition. I did more queries:
{code}
sqlCtx.sql("select id1, count(*) from joined group by id1 having count(*) >
1").collect()
{code}
This gives some results but this query return *1*
{code}
len(sqlCtx.sql("select * from joined where id1 = result").collect())
{code}
What's wrong ?
> Incorrect results when aggregate joined data
> --------------------------------------------
>
> Key: SPARK-12030
> URL: https://issues.apache.org/jira/browse/SPARK-12030
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.6.0
> Reporter: Maciej Bryński
> Priority: Critical
>
> I have following issue.
> I created 2 dataframes from JDBC (MySQL) and joined them (t1 has fk1 to t2)
> {code}
> t1 = sqlCtx.read.jdbc("jdbc:mysql://XXX", t1, id1, 0, size1, 200).cache()
> t2 = sqlCtx.read.jdbc("jdbc:mysql://XXX", t2, id2, 0, size1, 200).cache()
> joined = t1.join(t2, t1.fk1 == t2.id2, "left_outer")
> {code}
> Important: both table are cached, so results should be the same on every
> query.
> Then I did come counts:
> {code}
> t1.count() -> 5900729
> t1.registerTempTable("t1")
> sqlCtx.sql("select distinct(id1) from t1").count() -> 5900729
> t2.count() -> 54298
> joined.count() -> 5900729
> {code}
> And here magic begins - I counted distinct id1 from joined table
> {code}
> joined.registerTempTable("joined")
> sqlCtx.sql("select distinct(id1) from joined").count()
> {code}
> Results varies *(are different on every run)* between 5899000 and
> 5900000 but never are equal to 5900729.
> In addition. I did more queries:
> {code}
> sqlCtx.sql("select id1, count(*) from joined group by id1 having count(*) >
> 1").collect()
> {code}
> This gives some results but this query return *1*
> {code}
> len(sqlCtx.sql("select * from joined where id1 = result").collect())
> {code}
> What's wrong ?
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