From issues-return-186606-archive-asf-public=cust-asf.ponee.io@spark.apache.org Thu Mar 8 07:29:04 2018 Return-Path: X-Original-To: archive-asf-public@cust-asf.ponee.io Delivered-To: archive-asf-public@cust-asf.ponee.io Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by mx-eu-01.ponee.io (Postfix) with SMTP id 08382180676 for ; Thu, 8 Mar 2018 07:29:03 +0100 (CET) Received: (qmail 34620 invoked by uid 500); 8 Mar 2018 06:29:03 -0000 Mailing-List: contact issues-help@spark.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Delivered-To: mailing list issues@spark.apache.org Received: (qmail 34610 invoked by uid 99); 8 Mar 2018 06:29:03 -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; Thu, 08 Mar 2018 06:29:03 +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 ABB991800EB for ; Thu, 8 Mar 2018 06:29:02 +0000 (UTC) X-Virus-Scanned: Debian amavisd-new at spamd3-us-west.apache.org X-Spam-Flag: NO X-Spam-Score: -110.311 X-Spam-Level: X-Spam-Status: No, score=-110.311 tagged_above=-999 required=6.31 tests=[ENV_AND_HDR_SPF_MATCH=-0.5, RCVD_IN_DNSWL_MED=-2.3, SPF_PASS=-0.001, T_RP_MATCHES_RCVD=-0.01, USER_IN_DEF_SPF_WL=-7.5, USER_IN_WHITELIST=-100] autolearn=disabled 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 BOJ7xyyy8Bi6 for ; Thu, 8 Mar 2018 06:29:01 +0000 (UTC) Received: from mailrelay1-us-west.apache.org (mailrelay1-us-west.apache.org [209.188.14.139]) by mx1-lw-eu.apache.org (ASF Mail Server at mx1-lw-eu.apache.org) with ESMTP id 35E1E5F183 for ; Thu, 8 Mar 2018 06:29:01 +0000 (UTC) Received: from jira-lw-us.apache.org (unknown [207.244.88.139]) by mailrelay1-us-west.apache.org (ASF Mail Server at mailrelay1-us-west.apache.org) with ESMTP id 5A6C3E0308 for ; Thu, 8 Mar 2018 06:29:00 +0000 (UTC) Received: from jira-lw-us.apache.org (localhost [127.0.0.1]) by jira-lw-us.apache.org (ASF Mail Server at jira-lw-us.apache.org) with ESMTP id 11ABB253FD for ; Thu, 8 Mar 2018 06:29:00 +0000 (UTC) Date: Thu, 8 Mar 2018 06:29:00 +0000 (UTC) From: "Ajith S (JIRA)" To: issues@spark.apache.org Message-ID: In-Reply-To: References: Subject: [jira] [Created] (SPARK-23626) Spark DAGScheduler scheduling performance hindered on JobSubmitted Event MIME-Version: 1.0 Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: quoted-printable X-JIRA-FingerPrint: 30527f35849b9dde25b450d4833f0394 Ajith S created SPARK-23626: ------------------------------- Summary: Spark DAGScheduler scheduling performance hindered on= JobSubmitted Event Key: SPARK-23626 URL: https://issues.apache.org/jira/browse/SPARK-23626 Project: Spark Issue Type: Bug Components: Scheduler Affects Versions: 2.2.1 Reporter: Ajith S DAGScheduler becomes a bottleneck in cluster when multiple JobSubmitted eve= nts has to be processed as DAGSchedulerEventProcessLoop is single threaded = and it will block other tasks in queue like TaskCompletion. The JobSubmitted event is time consuming depending on the nature of the job= (Example: calculating parent stage dependencies, shuffle dependencies, par= titions) and thus it blocks all the events to be processed. =C2=A0 I see multiple JIRA referring to this behavior https://issues.apache.org/jira/browse/SPARK-2647 https://issues.apache.org/jira/browse/SPARK-4961 =C2=A0 Similarly in my cluster some jobs partition calculation is time consuming (= Similar to stack at SPARK-2647) hence it slows down the spark DAGSchedulerE= ventProcessLoop which results in user jobs to slowdown, even if its tasks a= re finished within seconds, as TaskCompletion Events are processed at a slo= wer rate due to blockage. -- This message was sent by Atlassian JIRA (v7.6.3#76005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org For additional commands, e-mail: issues-help@spark.apache.org