Return-Path: X-Original-To: archive-asf-public-internal@cust-asf2.ponee.io Delivered-To: archive-asf-public-internal@cust-asf2.ponee.io Received: from cust-asf.ponee.io (cust-asf.ponee.io [163.172.22.183]) by cust-asf2.ponee.io (Postfix) with ESMTP id 0791B200B40 for ; Wed, 1 Jun 2016 23:38:01 +0200 (CEST) Received: by cust-asf.ponee.io (Postfix) id 04915160A45; Wed, 1 Jun 2016 21:38:01 +0000 (UTC) Delivered-To: archive-asf-public@cust-asf.ponee.io Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by cust-asf.ponee.io (Postfix) with SMTP id 7946B160A4C for ; Wed, 1 Jun 2016 23:38:00 +0200 (CEST) Received: (qmail 51005 invoked by uid 500); 1 Jun 2016 21:37:59 -0000 Mailing-List: contact dev-help@kafka.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Reply-To: dev@kafka.apache.org Delivered-To: mailing list dev@kafka.apache.org Received: (qmail 50969 invoked by uid 99); 1 Jun 2016 21:37:59 -0000 Received: from arcas.apache.org (HELO arcas) (140.211.11.28) by apache.org (qpsmtpd/0.29) with ESMTP; Wed, 01 Jun 2016 21:37:59 +0000 Received: from arcas.apache.org (localhost [127.0.0.1]) by arcas (Postfix) with ESMTP id 614052C1F5A for ; Wed, 1 Jun 2016 21:37:59 +0000 (UTC) Date: Wed, 1 Jun 2016 21:37:59 +0000 (UTC) From: "Greg Fodor (JIRA)" To: dev@kafka.apache.org Message-ID: In-Reply-To: References: Subject: [jira] [Commented] (KAFKA-3769) KStream job spending 60% of time writing metrics MIME-Version: 1.0 Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: 7bit X-JIRA-FingerPrint: 30527f35849b9dde25b450d4833f0394 archived-at: Wed, 01 Jun 2016 21:38:01 -0000 [ https://issues.apache.org/jira/browse/KAFKA-3769?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15311179#comment-15311179 ] Greg Fodor commented on KAFKA-3769: ----------------------------------- Thanks Jay! Guozhang, what are your thoughts on instead of trying to reduce the granularity of the metrics, potentially having a way to just disable the process/latency metrics collection? I'm still pretty new to KStreams, and haven't used these metrics, but I'm guessing they will be used for occasionally tuning the job against production data but not necessarily for operational monitoring. (I could be wrong about this.) As such, it seems that you may want to just have a switch you flip when you are running in production that will disable the metrics and maximize the throughput of the job, and then turn it on selectively when you want to perform performance measurement. > KStream job spending 60% of time writing metrics > ------------------------------------------------ > > Key: KAFKA-3769 > URL: https://issues.apache.org/jira/browse/KAFKA-3769 > Project: Kafka > Issue Type: Bug > Components: streams > Affects Versions: 0.10.0.0 > Reporter: Greg Fodor > Assignee: Guozhang Wang > Priority: Critical > > I've been profiling a complex streams job, and found two major hotspots when writing metrics, which take up about 60% of the CPU time of the job. (!) A PR is attached. -- This message was sent by Atlassian JIRA (v6.3.4#6332)