Re: SparkSQL with large result size

case? > > Regards, > Gourav > > On Mon, May 2, 2016 at 5:59 PM, Ted Yu <yuzhih...@gmail.com> wrote: > >> That's my interpretation. >> >> On Mon, May 2, 2016 at 9:45 AM, Buntu Dev < <buntu...@gmail.com> >> buntu...@gmail.com> wrote: >> >&g

Re: pyspark dataframe sort issue

not defined. > > On Sat, May 7, 2016 at 11:48 PM, Buntu Dev <buntu...@gmail.com> wrote: > > I'm using pyspark dataframe api to sort by specific column and then > saving > > the dataframe as parquet file. But the resulting parquet file doesn't > seem > > to b

pyspark dataframe sort issue

I'm using pyspark dataframe api to sort by specific column and then saving the dataframe as parquet file. But the resulting parquet file doesn't seem to be sorted. Applying sort and doing a head() on the results shows the correct results sorted by 'value' column in desc order, as shown below:

Re: SparkSQL with large result size

this? On Mon, May 2, 2016 at 6:21 AM, Ted Yu <yuzhih...@gmail.com> wrote: > Please consider decreasing block size. > > Thanks > > > On May 1, 2016, at 9:19 PM, Buntu Dev <buntu...@gmail.com> wrote: > > > > I got a 10g limitation on the executors and operating on parq

SparkSQL with large result size

I got a 10g limitation on the executors and operating on parquet dataset with block size 70M with 200 blocks. I keep hitting the memory limits when doing a 'select * from t1 order by c1 limit 100' (ie, 1M). It works if I limit to say 100k. What are the options to save a large dataset without

Re: Dataframe fails for large resultsize

:01 PM, Krishna <research...@gmail.com> wrote: > I recently encountered similar network related errors and was able to fix > it by applying the ethtool updates decribed here [ > https://issues.apache.org/jira/plugins/servlet/mobile#issue/SPARK-5085] > > > On Friday, April 29

Re: Dataframe fails for large resultsize

e error I would ultimately want to store the result set as parquet. Are there any other options to handle this? Thanks! On Wed, Apr 27, 2016 at 11:10 AM, Buntu Dev <buntu...@gmail.com> wrote: > I got 14GB of parquet data and when trying to apply order by using spark > sql and save the f

Dataframe fails for large resultsize

I got 14GB of parquet data and when trying to apply order by using spark sql and save the first 1M rows but keeps failing with "Connection reset by peer: socket write error" on the executors. I've allocated about 10g to both driver and the executors along with setting the maxResultSize to 10g but

Re: How to estimate the size of dataframe using pyspark?

rovide a way to reproduce it (could generate fake > dataset)? > > On Sat, Apr 9, 2016 at 4:33 PM, Buntu Dev <buntu...@gmail.com> wrote: > > I've allocated about 4g for the driver. For the count stage, I notice the > > Shuffle Write to be 13.9 GB. > > > > On

Re: Graphframes pattern causing java heap space errors

gt; Looks like the exception occurred on driver. > > Consider increasing the values for the following config: > > conf.set("spark.driver.memory", "10240m") > conf.set("spark.driver.maxResultSize", "2g") > > Cheers > > On Sat, Apr 9, 20

Re: Graphframes pattern causing java heap space errors

; > Pozdrawiam, > Jacek Laskowski > > https://medium.com/@jaceklaskowski/ > Mastering Apache Spark http://bit.ly/mastering-apache-spark > Follow me at https://twitter.com/jaceklaskowski > > > On Sat, Apr 9, 2016 at 7:51 PM, Buntu Dev <buntu...@gmail.com> wrote: > &

Graphframes pattern causing java heap space errors

I'm running this motif pattern against 1.5M vertices (5.5mb) and 10M (60mb) edges: tgraph.find("(a)-[]->(b); (c)-[]->(b); (c)-[]->(d)") I keep running into Java heap space errors: ~ ERROR actor.ActorSystemImpl: Uncaught fatal error from thread

Re: How to estimate the size of dataframe using pyspark?

I've allocated about 4g for the driver. For the count stage, I notice the Shuffle Write to be 13.9 GB. On Sat, Apr 9, 2016 at 11:43 AM, Ndjido Ardo BAR <ndj...@gmail.com> wrote: > What's the size of your driver? > On Sat, 9 Apr 2016 at 20:33, Buntu Dev <buntu...@gmail.com> wr

Re: How to estimate the size of dataframe using pyspark?

Actually, df.show() works displaying 20 rows but df.count() is the one which is causing the driver to run out of memory. There are just 3 INT columns. Any idea what could be the reason? On Sat, Apr 9, 2016 at 10:47 AM, wrote: > You seem to have a lot of column :-) ! >

Re: Dataframe to parquet using hdfs or parquet block size

I tried setting both the hdfs and parquet block size but write to parquet did not seem to have had any effect on the total number of blocks or the average block size. Here is what I did: sqlContext.setConf("dfs.blocksize", "134217728") sqlContext.setConf("parquet.block.size", "134217728")

Re: Rule Engine for Spark

You may want to read this post regarding Spark with Drools: http://blog.cloudera.com/blog/2015/11/how-to-build-a-complex-event-processing-app-on-apache-spark-and-drools/ On Wed, Nov 4, 2015 at 8:05 PM, Daniel Mahler wrote: > I am not familiar with any rule engines on Spark

Re: Algebird using spark-shell

Thanks.. I was using Scala 2.11.1 and was able to use algebird-core_2.10-0.1.11.jar with spark-shell. On Thu, Oct 30, 2014 at 8:22 AM, Ian O'Connell i...@ianoconnell.com wrote: Whats the error with the 2.10 version of algebird? On Thu, Oct 30, 2014 at 12:49 AM, thadude ohpre...@yahoo.com

Re: Error while running Streaming examples - no snappyjava in java.library.path

Thanks Akhil. On Mon, Oct 20, 2014 at 1:57 AM, Akhil Das ak...@sigmoidanalytics.com wrote: Its a known bug in JDK7 and OSX's naming convention, here's how to resolve it: 1. Get the Snappy jar file from http://central.maven.org/maven2/org/xerial/snappy/snappy-java/ 2. Copy the appropriate

Re: How to save ReceiverInputDStream to Hadoop using saveAsNewAPIHadoopFile

Thanks Sean, but I'm importing org.apache.spark.streaming. StreamingContext._ Here are the spark imports: import org.apache.spark.streaming._ import org.apache.spark.streaming.StreamingContext._ import org.apache.spark.streaming.kafka._ import org.apache.spark.SparkConf val stream

Re: Kafka-HDFS to store as Parquet format

impala, then it may allow if the schema changes are append only. Otherwise existing Parquet files have to be migrated to new schema. - Original Message - From: Buntu Dev buntu...@gmail.com To: Soumitra Kumar kumar.soumi...@gmail.com Cc: u...@spark.incubator.apache.org Sent: Tuesday

Re: Spark Streaming: No parallelism in writing to database (MySQL)

Thanks for the update.. I'm interested in writing the results to MySQL as well, can you share some light or code sample on how you setup the driver/connection pool/etc.? On Thu, Sep 25, 2014 at 4:00 PM, maddenpj madde...@gmail.com wrote: Update for posterity, so once again I solved the problem

Re: SchemaRDD select expression

the same thing in 1.0.0 using DSL only. Just curious, why don't you use the hql() / sql() methods and pass a query string in? [1] https://github.com/apache/spark/pull/1211/files On Thu, Jul 31, 2014 at 2:20 PM, Buntu Dev buntu...@gmail.com wrote: Thanks Zongheng for the pointer

Re: SchemaRDD select expression

Thanks Michael for confirming! On Thu, Jul 31, 2014 at 2:43 PM, Michael Armbrust mich...@databricks.com wrote: The performance should be the same using the DSL or SQL strings. On Thu, Jul 31, 2014 at 2:36 PM, Buntu Dev buntu...@gmail.com wrote: I was not sure if registerAsTable