Return-Path: X-Original-To: apmail-hive-issues-archive@minotaur.apache.org Delivered-To: apmail-hive-issues-archive@minotaur.apache.org Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by minotaur.apache.org (Postfix) with SMTP id B82BC180B6 for ; Fri, 17 Jul 2015 12:58:07 +0000 (UTC) Received: (qmail 20390 invoked by uid 500); 17 Jul 2015 12:58:04 -0000 Delivered-To: apmail-hive-issues-archive@hive.apache.org Received: (qmail 20366 invoked by uid 500); 17 Jul 2015 12:58:04 -0000 Mailing-List: contact issues-help@hive.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Reply-To: dev@hive.apache.org Delivered-To: mailing list issues@hive.apache.org Received: (qmail 20356 invoked by uid 99); 17 Jul 2015 12:58:04 -0000 Received: from arcas.apache.org (HELO arcas.apache.org) (140.211.11.28) by apache.org (qpsmtpd/0.29) with ESMTP; Fri, 17 Jul 2015 12:58:04 +0000 Date: Fri, 17 Jul 2015 12:58:04 +0000 (UTC) From: "Xuefu Zhang (JIRA)" To: issues@hive.apache.org Message-ID: In-Reply-To: References: Subject: [jira] [Resolved] (HIVE-11276) Optimization around job submission and adding jars [Spark Branch] MIME-Version: 1.0 Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: 7bit X-JIRA-FingerPrint: 30527f35849b9dde25b450d4833f0394 [ https://issues.apache.org/jira/browse/HIVE-11276?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Xuefu Zhang resolved HIVE-11276. -------------------------------- Resolution: Not A Problem > Optimization around job submission and adding jars [Spark Branch] > ----------------------------------------------------------------- > > Key: HIVE-11276 > URL: https://issues.apache.org/jira/browse/HIVE-11276 > Project: Hive > Issue Type: Sub-task > Components: Spark > Affects Versions: 1.1.0 > Reporter: Xuefu Zhang > Assignee: Chengxiang Li > > It seems that Hive on Spark has some room for performance improvement on job submission. Specifically, we are calling refreshLocalResources() for every job submission despite there is are no changes in the jar list. Since Hive on Spark is reusing the containers in the whole user session, we might be able to optimize that. > We do need to take into consideration the case of dynamic allocation, in which new executors might be added. > This task is some R&D in this area. -- This message was sent by Atlassian JIRA (v6.3.4#6332)