Joseph Sun created SPARK-12802:
----------------------------------
Summary: The DataFrame.rdd not return same result
Key: SPARK-12802
URL: https://issues.apache.org/jira/browse/SPARK-12802
Project: Spark
Issue Type: Bug
Components: Spark Core, SQL
Affects Versions: 1.5.2
Environment: 3 servers of centos7, cluster mode
Reporter: Joseph Sun
run spark-shell and typeing following codes.
> import org.apache.spark.sql.types._
> val schema = StructType(StructField("id",IntegerType,true)::Nil)
> val rdd = sc.parallelize((0 to 10000)).map(Row(_))
> val df = sqlContext.createDataFrame(rdd,schema)
> df.registerTempTable("test")
> sqlContext.cacheTable("test")
> sqlContext.sql("select * from test limit 2").collect()
show Array[org.apache.spark.sql.Row] = Array([0], [1])
> sqlContext.sql("select * from test limit 2").rdd.collect()
run the code one more times,the result is not consistent.
some times the result is : Array[org.apache.spark.sql.Row] = Array([0], [1])
or: Array[org.apache.spark.sql.Row] = Array([2500], [2501])
why?
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
