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https://issues.apache.org/jira/browse/SPARK-19102?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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XiaodongCui updated SPARK-19102:
--------------------------------
Description:
the problem is the result of the code blow that the second column's value
is not the same.the second sql result is 10000 times bigger than the first
sql result.the bug is only reappear in the format like sum(a * b),count
(distinct c)
DataFrame
df1=sqlContext.read().parquet("hdfs://cdh01:8020/sandboxdata_A/test/a");
df1.registerTempTable("hd_salesflat");
DataFrame cube5 = sqlContext.sql("SELECT areacode1,
SUM(quantity*unitprice) AS sumprice FROM hd_salesflat GROUP BY areacode1");
DataFrame cube6 = sqlContext.sql("SELECT areacode1,
SUM(quantity*unitprice) AS sumprice, COUNT(DISTINCT transno) FROM hd_salesflat
GROUP BY areacode1");
cube5.show(50);
cube6.show(50);
was:
the problem is the result of the code blow that is not the same.the second
sql result is 10000 times bigger than the first sql result.the bug is only
reappear in the format like sum(a * b),count (distinct c)
DataFrame
df1=sqlContext.read().parquet("hdfs://cdh01:8020/sandboxdata_A/test/a");
df1.registerTempTable("hd_salesflat");
DataFrame cube5 = sqlContext.sql("SELECT areacode1,
SUM(quantity*unitprice) AS sumprice FROM hd_salesflat GROUP BY areacode1");
DataFrame cube6 = sqlContext.sql("SELECT areacode1,
SUM(quantity*unitprice) AS sumprice, COUNT(DISTINCT transno) FROM hd_salesflat
GROUP BY areacode1");
cube5.show(50);
cube6.show(50);
> Accuracy error of spark SQL results
> -----------------------------------
>
> Key: SPARK-19102
> URL: https://issues.apache.org/jira/browse/SPARK-19102
> Project: Spark
> Issue Type: Bug
> Components: Spark Core, SQL
> Affects Versions: 1.6.0, 1.6.1
> Environment: Spark 1.6.0, Hadoop 2.6.0,JDK 1.8,CentOS6.6
> Reporter: XiaodongCui
>
> the problem is the result of the code blow that the second column's value
> is not the same.the second sql result is 10000 times bigger than the first
> sql result.the bug is only reappear in the format like sum(a * b),count
> (distinct c)
> DataFrame
> df1=sqlContext.read().parquet("hdfs://cdh01:8020/sandboxdata_A/test/a");
> df1.registerTempTable("hd_salesflat");
> DataFrame cube5 = sqlContext.sql("SELECT areacode1,
> SUM(quantity*unitprice) AS sumprice FROM hd_salesflat GROUP BY areacode1");
> DataFrame cube6 = sqlContext.sql("SELECT areacode1,
> SUM(quantity*unitprice) AS sumprice, COUNT(DISTINCT transno) FROM
> hd_salesflat GROUP BY areacode1");
> cube5.show(50);
> cube6.show(50);
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