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From Aljoscha Krettek <aljos...@apache.org>
Subject Re: Flink parquet read.write performance
Date Fri, 18 Aug 2017 16:14:26 GMT
Hi Billy,

Do you also have the data (picture) from the "Timeline" tab of the completed job? This would
give some hints about how long that other DataSource (with chain) was active. It might be
that the sink is waiting for the other input to become online.

Best,
Aljoscha

> On 18. Aug 2017, at 14:45, Newport, Billy <Billy.Newport@gs.com> wrote:
> 
> Hi,
>  
> I’m trying to figure out why reading and writing ~5GB worth of parquet files seems
to take 3-4 minutes with 10 TaskManagers, 2 slots, 20GB memory, 20 Parallelism. I’ve copied
in the execution plan the taskmanager times below. Other details include that we’re reading
20 snappy compresed parquet files each ~240MB each. (see below)
>  
> I’m trying to use this for a milestoning logic where we take new avro files from staging
and join with the existing milestoned parquet data. I have a small staging file with only
about 1500 records inside so I reduce the number of records sent to the cogroup in order to
make this faster. To do this, I’m basically reading in GenericRecords from parquet files
twice, once to filter out for “live” records where we then further filter the records
for ones with keys matching what we found in a separate avro file. This is so reduction of
records makes that part of the plan total to 1 minute 58 secs.
>  
> The concern is the other records with non-live/not-matching-keys. In theory, I expect
this to be fast since it’s just chaining the operations across all the way through to the
sink. However, this part takes about 4 minutes. We’re not doing anything different from
the other Datasource aside from mapping a DataSet<GenericRecord> to a Tuple2<Short,GenericRecord>
where the short is a bitmap value mapping to where the record needs to be written. 
>  
> Other notes:
> I checked the backpressure on the datasource->filter->map->map and it was OK.
I’m not sure what else could be holding it up.
> I also profiled it when I ran it on a single task manager single slot and it seems to
spend most of the time waiting.
>  
> Any ideas? Instead of truly chaining is it writing to disk and serializing multiple times
inside each operation?
>  
> Data Source :
> hdfs dfs -du -h <folder_name>
> 240.2 M  <folder_name>/0_partMapper-m-00013.snappy.parquet
> 237.2 M  <folder_name>/10_partMapper-m-00019.snappy.parquet
> 241.9 M  <folder_name>/11_partMapper-m-00002.snappy.parquet
> 243.3 M  <folder_name>/12_partMapper-m-00000.snappy.parquet
> 238.2 M  <folder_name>/13_partMapper-m-00016.snappy.parquet
> 241.7 M  <folder_name>/14_partMapper-m-00003.snappy.parquet
> 241.0 M  <folder_name>/15_partMapper-m-00006.snappy.parquet
> 240.3 M  <folder_name>/16_partMapper-m-00012.snappy.parquet
> 240.3 M  <folder_name>/17_partMapper-m-00011.snappy.parquet
> 239.5 M  <folder_name>/18_partMapper-m-00014.snappy.parquet
> 237.6 M  <folder_name>/19_partMapper-m-00018.snappy.parquet
> 240.7 M  <folder_name>/1_partMapper-m-00009.snappy.parquet
> 240.7 M  <folder_name>/20_partMapper-m-00008.snappy.parquet
> 236.5 M  <folder_name>/2_partMapper-m-00020.snappy.parquet
> 242.1 M  <folder_name>/3_partMapper-m-00001.snappy.parquet
> 241.7 M  <folder_name>/4_partMapper-m-00004.snappy.parquet
> 240.5 M  <folder_name>/5_partMapper-m-00010.snappy.parquet
> 241.7 M  <folder_name>/6_partMapper-m-00005.snappy.parquet
> 239.1 M  <folder_name>/7_partMapper-m-00015.snappy.parquet
> 237.9 M  <folder_name>/8_partMapper-m-00017.snappy.parquet
> 240.8 M  <folder_name>/9_partMapper-m-00007.snappy.parquet
>  
>  
> yarn-session.sh -nm "delp_uat-IMD_Trading_v1_PROD_PerfTest-REFINER_INGEST"  -jm 4096
-tm 20480 -s 2 -n 10  -d]
>  
>  
> <image001.png>
>  
> <image002.png>
>  
>  
> Thanks,
>  
> Regina


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