From user-return-77279-apmail-spark-user-archive=spark.apache.org@spark.apache.org Fri Feb 8 16:09:28 2019 Return-Path: X-Original-To: apmail-spark-user-archive@minotaur.apache.org Delivered-To: apmail-spark-user-archive@minotaur.apache.org Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by minotaur.apache.org (Postfix) with SMTP id B6692186C4 for ; Fri, 8 Feb 2019 16:09:28 +0000 (UTC) Received: (qmail 20264 invoked by uid 500); 8 Feb 2019 16:09:17 -0000 Delivered-To: apmail-spark-user-archive@spark.apache.org Received: (qmail 20144 invoked by uid 500); 8 Feb 2019 16:09:17 -0000 Mailing-List: contact user-help@spark.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Delivered-To: mailing list user@spark.apache.org Received: (qmail 20134 invoked by uid 99); 8 Feb 2019 16:09:17 -0000 Received: from pnap-us-west-generic-nat.apache.org (HELO spamd3-us-west.apache.org) (209.188.14.142) by apache.org (qpsmtpd/0.29) with ESMTP; Fri, 08 Feb 2019 16:09:17 +0000 Received: from localhost (localhost [127.0.0.1]) by spamd3-us-west.apache.org (ASF Mail Server at spamd3-us-west.apache.org) with ESMTP id 40478181A36 for ; Fri, 8 Feb 2019 16:09:17 +0000 (UTC) X-Virus-Scanned: Debian amavisd-new at spamd3-us-west.apache.org X-Spam-Flag: NO X-Spam-Score: 3.079 X-Spam-Level: *** X-Spam-Status: No, score=3.079 tagged_above=-999 required=6.31 tests=[DKIMWL_WL_MED=-0.001, DKIM_SIGNED=0.1, DKIM_VALID=-0.1, DKIM_VALID_AU=-0.1, DKIM_VALID_EF=-0.1, HTML_IMAGE_ONLY_24=1.282, HTML_MESSAGE=2, RCVD_IN_DNSWL_NONE=-0.0001, RCVD_IN_MSPIKE_H2=-0.001, SPF_PASS=-0.001] autolearn=disabled Authentication-Results: spamd3-us-west.apache.org (amavisd-new); dkim=pass (2048-bit key) header.d=gmail.com Received: from mx1-lw-eu.apache.org ([10.40.0.8]) by localhost (spamd3-us-west.apache.org [10.40.0.10]) (amavisd-new, port 10024) with ESMTP id DhQCWluc5aOF for ; Fri, 8 Feb 2019 16:09:15 +0000 (UTC) Received: from mail-wr1-f46.google.com (mail-wr1-f46.google.com [209.85.221.46]) by mx1-lw-eu.apache.org (ASF Mail Server at mx1-lw-eu.apache.org) with ESMTPS id 2A7265F181 for ; Fri, 8 Feb 2019 16:09:15 +0000 (UTC) Received: by mail-wr1-f46.google.com with SMTP id z3so4175868wrv.3 for ; Fri, 08 Feb 2019 08:09:15 -0800 (PST) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=gmail.com; s=20161025; h=mime-version:references:in-reply-to:from:date:message-id:subject:to; bh=5eF4bZ0jivIFVpV1EkM9FA1VHl13/vqmlF6UIIyT4q4=; b=Hz4aCQK5gUFmG6C9MxMNAc49P8EjNhVstMVW7c42z3MkAZNPVlYOX5zhW5HsFXfEXL StWzLQcV4V73gfXcibGI7ItnQEybGeEto0RbkSjR0Isrw5wfLRTYc8CGnYsAAk6dtU7o YTVd7eOPomJJDoegyiYXEBV8CigC3Gb2llPi8oQG+rywlGdXdt1UT+EpM7rW1yP2lFjH +tPfp7hfpKwkumycSbRKygh5JSeSFnYlPOLr/0FOfbuJchxkfLd9U9ZWyxWQy4QX+Qjc vm42JLx9zIFCrD3papePbnMOY2WsW30Fe1xUjSvAO3DDpt5RENFmsoPmAeqYSXX5zT3A zQ5Q== X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=1e100.net; s=20161025; h=x-gm-message-state:mime-version:references:in-reply-to:from:date :message-id:subject:to; bh=5eF4bZ0jivIFVpV1EkM9FA1VHl13/vqmlF6UIIyT4q4=; b=uRD53/0909ugJGBPZt/zfsIHj7Y3ygDkdF367w9n1PtXUA5QyCikPSjGpE9ezg34+2 t/carXbrcNhCTqqAnjRveTHvwONHax/kaaCHY2B8DK6XEUMIU9PqlRatnk6v/5Bqzrb4 yt/7ODUCPIY1dvExz9LH2KctL623+Lsj3v7qOIQFFS3FYhSzQQHINhJWdxd5xWZYNgFy GQ7/iN1tvLLlMt8/bmp18AGXKqsluc6yY3xsL0aEjjWzRtTKpH+xkEQ4Icd5flzo5NlK vVHkO+Mj1Bn5CzP90bZo1D2dYV8iok3Iu2VNx1iF2m8/MIGWnoPgIXnykW1uYxFOjexp VbNA== X-Gm-Message-State: AHQUAuYH37NEUnpL18XK0/6eHxIxkwgFHYUgjAn2mM2vKyEoztxOmPtN TfXc4b3Ac3dpxIH4CRJ2BcvVQ8+z0U51i07MkglNyg== X-Google-Smtp-Source: AHgI3IZZArJ0UX9re+pvyvVzZoJVB9Eauosl/ECmouo+TCMx9sZ6xDbX32UliGih0tCgoaTIyZ+hNHU174kZtBfmCso= X-Received: by 2002:adf:9ec8:: with SMTP id b8mr18075151wrf.164.1549642153952; Fri, 08 Feb 2019 08:09:13 -0800 (PST) MIME-Version: 1.0 References: In-Reply-To: From: Pedro Tuero Date: Fri, 8 Feb 2019 13:09:02 -0300 Message-ID: Subject: Re: Spark 2.4 partitions and tasks To: user@spark.apache.org Content-Type: multipart/related; boundary="0000000000001e914c0581642e2e" --0000000000001e914c0581642e2e Content-Type: multipart/alternative; boundary="0000000000001e914b0581642e2d" --0000000000001e914b0581642e2d Content-Type: text/plain; charset="UTF-8" Content-Transfer-Encoding: quoted-printable I did a repartition to 10000 (hardcoded) before the keyBy and it ends in 1.2 minutes. The questions remain open, because I don't want to harcode paralellism. El vie., 8 de feb. de 2019 a la(s) 12:50, Pedro Tuero (tueropedro@gmail.com= ) escribi=C3=B3: > 128 is the default parallelism defined for the cluster. > The question now is why keyBy operation is using default parallelism > instead of the number of partition of the RDD created by the previous ste= p > (5580). > Any clues? > > El jue., 7 de feb. de 2019 a la(s) 15:30, Pedro Tuero ( > tueropedro@gmail.com) escribi=C3=B3: > >> Hi, >> I am running a job in spark (using aws emr) and some stages are taking a >> lot more using spark 2.4 instead of Spark 2.3.1: >> >> Spark 2.4: >> [image: image.png] >> >> Spark 2.3.1: >> [image: image.png] >> >> With Spark 2.4, the keyBy operation take more than 10X what it took with >> Spark 2.3.1 >> It seems to be related to the number of tasks / partitions. >> >> Questions: >> - Is it not supposed that the number of task of a job is related to >> number of parts of the RDD left by the previous job? Did that change in >> version 2.4?? >> - Which tools/ configuration may I try, to reduce this aberrant downgrad= e >> of performance?? >> >> Thanks. >> Pedro. >> > --0000000000001e914b0581642e2d Content-Type: text/html; charset="UTF-8" Content-Transfer-Encoding: quoted-printable
I did a repartition to 10000 (hardcoded) before the k= eyBy and it ends in 1.2 minutes.
The questions remain open, becau= se I don't want to harcode paralellism.

El vie., 8 de feb. de 2019 a= la(s) 12:50, Pedro Tuero (tueroped= ro@gmail.com) escribi=C3=B3:
128 is the default parallelism defin= ed for the cluster.
The question now is why keyBy operation = is using default parallelism instead of the number of partition of the RDD = created by the previous step (5580).
Any clues?

El = jue., 7 de feb. de 2019 a la(s) 15:30, Pedro Tuero (tueropedro@gmail.com) escribi=C3=B3:=
Hi,
I am running a job in spark (using aws emr) and s= ome stages are taking a lot more using spark=C2=A0 2.4 instead of Spark 2.3= .1:

Spark 2.4:
3D"image.png"

Spark 2.3.1:
3D"image.png"

With Spark 2.4, the keyBy operation take more than 10X what it took = with Spark 2.3.1
It seems to be related to the number of task= s / partitions.

Questions:
- Is it = not supposed that the number of task of a job is related to number of parts= of the RDD left by the previous job? Did that change in version 2.4??
- Which tools/ configuration may I try, to reduce this aberrant downg= rade of performance??

Thanks.
Pedro.
=
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