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L. C. Hsieh commented on SPARK-32888: ------------------------------------- Yes, there is difference. But it is due to reading file and reading from RDD/Dataset. When reading file, we definitely know which line is first line, we can remove it. When we read from RDD/Dataset, we don't know which lines are first files in the reading files. So the best we can do, is just remove the lines same as the first line in the RDD/Dataset. > reading a parallized rdd with two identical records results in a zero count > df when read via spark.read.csv > ----------------------------------------------------------------------------------------------------------- > > Key: SPARK-32888 > URL: https://issues.apache.org/jira/browse/SPARK-32888 > Project: Spark > Issue Type: Documentation > Components: Spark Core > Affects Versions: 2.4.5, 2.4.6, 2.4.7, 3.0.0, 3.0.1 > Reporter: Punit Shah > Assignee: L. C. Hsieh > Priority: Minor > Fix For: 2.4.8, 3.0.2, 3.1.0 > > > * Imagine a two-row csv file like so (where the header and first record are > duplicate rows): > aaa,bbb > aaa,bbb > * The following is pyspark code > * create a parallelized rdd like: {color:#FF0000}prdd = > spark.read.text("test.csv").rdd.flatMap(lambda x : x){color} > * {color:#172b4d}create a df like so: {color:#de350b}mydf = > spark.read.csv(prdd, header=True){color}{color} > * {color:#172b4d}{color:#de350b}df.count(){color:#172b4d} will result in a > record count of zero (when it should be 1){color}{color}{color} -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org