Re: Spark Number of Partitions Recommendations
Yes, I forgot to mention I chose prime number as a modulo for hash function because my keys are usually strings and spark calculates particular partitiion using key hash(see HashPartitioner.scala) So, to avoid big number of collisions(when many keys located in few partition) it is common to use prime number in modulo. But it makes sense only for String keys offcourse, because of hash function. If yuo have different hash function for key of different type you can use any other modulo instead prime number. I like this discussion on this topic http://stackoverflow.com/questions/1145217/why-should-hash-functions-use-a-prime-number-modulus -- Яндекс.Почта — надёжная почта http://mail.yandex.ru/neo2/collect/?exp=1&t=1 02.08.2015, 00:14, "Ruslan Dautkhanov" : > You should also take into account amount of memory that you plan to use. > It's advised not to give too much memory for each executor .. otherwise GC > overhead will go up. > > Btw, why prime numbers? > > -- > Ruslan Dautkhanov > > On Wed, Jul 29, 2015 at 3:31 AM, ponkin wrote: >> Hi Rahul, >> >> Where did you see such a recommendation? >> I personally define partitions with the following formula >> >> partitions = nextPrimeNumberAbove( K*(--num-executors * --executor-cores ) ) >> >> where >> nextPrimeNumberAbove(x) - prime number which is greater than x >> K - multiplicator to calculate start with 1 and encrease untill join >> perfomance start to degrade >> >> -- >> View this message in context: >> http://apache-spark-user-list.1001560.n3.nabble.com/Spark-Number-of-Partitions-Recommendations-tp24022p24059.html >> >> Sent from the Apache Spark User List mailing list archive at Nabble.com. >> >> - >> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >> For additional commands, e-mail: user-h...@spark.apache.org - To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
Re: Spark Number of Partitions Recommendations
You should also take into account amount of memory that you plan to use. It's advised not to give too much memory for each executor .. otherwise GC overhead will go up. Btw, why prime numbers? -- Ruslan Dautkhanov On Wed, Jul 29, 2015 at 3:31 AM, ponkin wrote: > Hi Rahul, > > Where did you see such a recommendation? > I personally define partitions with the following formula > > partitions = nextPrimeNumberAbove( K*(--num-executors * --executor-cores ) > ) > > where > nextPrimeNumberAbove(x) - prime number which is greater than x > K - multiplicator to calculate start with 1 and encrease untill join > perfomance start to degrade > > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/Spark-Number-of-Partitions-Recommendations-tp24022p24059.html > Sent from the Apache Spark User List mailing list archive at Nabble.com. > > - > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > >
Re: Spark Number of Partitions Recommendations
imho, you need to take into account size of your data too if your cluster is relatively small, you may cause memory pressure on your executors if trying to repartition to some #cores connected number of partitions better to take some max between initial number of partitions(assuming your data is on hdfs with 64Mb block size) and between number you get from your formula On 29 July 2015 at 12:31, ponkin wrote: > Hi Rahul, > > Where did you see such a recommendation? > I personally define partitions with the following formula > > partitions = nextPrimeNumberAbove( K*(--num-executors * --executor-cores ) > ) > > where > nextPrimeNumberAbove(x) - prime number which is greater than x > K - multiplicator to calculate start with 1 and encrease untill join > perfomance start to degrade > > > > > -- > View this message in context: > http://apache-spark-user-list.1001560.n3.nabble.com/Spark-Number-of-Partitions-Recommendations-tp24022p24059.html > Sent from the Apache Spark User List mailing list archive at Nabble.com. > > - > To unsubscribe, e-mail: user-unsubscr...@spark.apache.org > For additional commands, e-mail: user-h...@spark.apache.org > >
Re: Spark Number of Partitions Recommendations
Hi Rahul, Where did you see such a recommendation? I personally define partitions with the following formula partitions = nextPrimeNumberAbove( K*(--num-executors * --executor-cores ) ) where nextPrimeNumberAbove(x) - prime number which is greater than x K - multiplicator to calculate start with 1 and encrease untill join perfomance start to degrade -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Spark-Number-of-Partitions-Recommendations-tp24022p24059.html Sent from the Apache Spark User List mailing list archive at Nabble.com. - To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
