Hi All, I might find a related issue on jira:
https://issues.apache.org/jira/browse/SPARK-15678 This issue is closed, may be we should reopen it. Thanks Cheers Gen On Wed, Feb 22, 2017 at 1:57 PM, gen tang <gen.tan...@gmail.com> wrote: > Hi All, > > I found a strange bug which is related with reading data from a updated > path and cache operation. > Please consider the following code: > > import org.apache.spark.sql.DataFrame > > def f(data: DataFrame): DataFrame = { > val df = data.filter("id>10") > df.cache > df.count > df > } > > f(spark.range(100).asInstanceOf[DataFrame]).count // output 89 which is > correct > f(spark.range(1000).asInstanceOf[DataFrame]).count // output 989 which is > correct > > val dir = "/tmp/test" > spark.range(100).write.mode("overwrite").parquet(dir) > val df = spark.read.parquet(dir) > df.count // output 100 which is correct > f(df).count // output 89 which is correct > > spark.range(1000).write.mode("overwrite").parquet(dir) > val df1 = spark.read.parquet(dir) > df1.count // output 1000 which is correct, in fact other operation expect > df1.filter("id>10") return correct result. > f(df1).count // output 89 which is incorrect > > In fact when we use df1.filter("id>10"), spark will however use old cached > dataFrame > > Any idea? Thanks a lot > > Cheers > Gen >
