What version of Spark are you using and how many output files does the
job writes out?
By default, Spark versions before 1.6 (not including) writes Parquet
summary files when committing the job. This process reads footers from
all Parquet files in the destination directory and merges them together.
This can be particularly bad if you are appending a small amount of data
to a large existing Parquet dataset.
If that's the case, you may disable Parquet summary files by setting
Hadoop configuration " parquet.enable.summary-metadata" to false.
We've disabled it by default since 1.6.0
Cheng
On 10/21/16 1:47 PM, Chetan Khatri wrote:
Hello Spark Users,
I am writing around 10 GB of Processed Data to Parquet where having 1
TB of HDD and 102 GB of RAM, 16 vCore machine on Google Cloud.
Every time, i write to parquet. it shows on Spark UI that stages
succeeded but on spark shell it hold context on wait mode for almost
10 mins. then it clears broadcast, accumulator shared variables.
Can we sped up this thing ?
Thanks.
--
Yours Aye,
Chetan Khatri.
M.+91 76666 80574
Data Science Researcher
INDIA
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