Hi Jerry, Looks like it is a Python-specific issue. Can you create a JIRA?
Thanks, Yin On Mon, Sep 21, 2015 at 8:56 AM, Jerry Lam <chiling...@gmail.com> wrote: > Hi Spark Developers, > > I just ran some very simple operations on a dataset. I was surprise by the > execution plan of take(1), head() or first(). > > For your reference, this is what I did in pyspark 1.5: > df=sqlContext.read.parquet("someparquetfiles") > df.head() > > The above lines take over 15 minutes. I was frustrated because I can do > better without using spark :) Since I like spark, so I tried to figure out > why. It seems the dataframe requires 3 stages to give me the first row. It > reads all data (which is about 1 billion rows) and run Limit twice. > > Instead of head(), show(1) runs much faster. Not to mention that if I do: > > df.rdd.take(1) //runs much faster. > > Is this expected? Why head/first/take is so slow for dataframe? Is it a > bug in the optimizer? or I did something wrong? > > Best Regards, > > Jerry >