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 08E42200C49 for ; Fri, 17 Mar 2017 22:55:47 +0100 (CET) Received: by cust-asf.ponee.io (Postfix) id 076CD160B80; Fri, 17 Mar 2017 21:55:47 +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 5208D160B70 for ; Fri, 17 Mar 2017 22:55:46 +0100 (CET) Received: (qmail 48443 invoked by uid 500); 17 Mar 2017 21:55:44 -0000 Mailing-List: contact issues-help@impala.incubator.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Reply-To: dev@impala.incubator.apache.org Delivered-To: mailing list issues@impala.incubator.apache.org Received: (qmail 48432 invoked by uid 99); 17 Mar 2017 21:55:44 -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, 17 Mar 2017 21:55:44 +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 B809A18063D for ; Fri, 17 Mar 2017 21:55:43 +0000 (UTC) X-Virus-Scanned: Debian amavisd-new at spamd3-us-west.apache.org X-Spam-Flag: NO X-Spam-Score: 0.651 X-Spam-Level: X-Spam-Status: No, score=0.651 tagged_above=-999 required=6.31 tests=[RP_MATCHES_RCVD=-0.001, SPF_NEUTRAL=0.652] autolearn=disabled Received: from mx1-lw-us.apache.org ([10.40.0.8]) by localhost (spamd3-us-west.apache.org [10.40.0.10]) (amavisd-new, port 10024) with ESMTP id yjqxJZtF2iVT for ; Fri, 17 Mar 2017 21:55:42 +0000 (UTC) Received: from mailrelay1-us-west.apache.org (mailrelay1-us-west.apache.org [209.188.14.139]) by mx1-lw-us.apache.org (ASF Mail Server at mx1-lw-us.apache.org) with ESMTP id 5A0F45FD28 for ; Fri, 17 Mar 2017 21:55:42 +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 CC924E008E for ; Fri, 17 Mar 2017 21:55:41 +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 832602434F for ; Fri, 17 Mar 2017 21:55:41 +0000 (UTC) Date: Fri, 17 Mar 2017 21:55:41 +0000 (UTC) From: "Alexander Behm (JIRA)" To: issues@impala.incubator.apache.org Message-ID: In-Reply-To: References: Subject: [jira] [Updated] (IMPALA-5095) Use parquet::Statistics for simple min/max aggregates MIME-Version: 1.0 Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: 7bit X-JIRA-FingerPrint: 30527f35849b9dde25b450d4833f0394 archived-at: Fri, 17 Mar 2017 21:55:47 -0000 [ https://issues.apache.org/jira/browse/IMPALA-5095?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Alexander Behm updated IMPALA-5095: ----------------------------------- Description: {code} select min(int_col), max(bigint_col) from parquet_table; select min(int_col), max(bigint_col) from parquet_table group by partition_col; select min(int_col), max(int_col) from parquet_table group by partition_col; <--- case a little trickier because int_col refd twice {code} The slot values for int_col and bigint_col can be directly filled in from the parquet::Statistics, assuming stats are available for both columns. No columns need to be scanned/materialized. This JIRA focuses on implementing this optimization in the simple case where all scanned columns feed into min/max aggregates and where all columns have parquet::Statistics. Those conditions can be relaxed, but should be addressed separately. This optimization opportunity must be detected by the planner and is not applicable when there are scan predicates. was: {code} select min(int_col), max(bigint_col) from parquet_table; select min(int_col), max(bigint_col) from parquet_table group by partition_col; {code} The slot values for int_col and bigint_col can be directly filled in from the parquet::Statistics, assuming stats are available for both columns. No columns need to be scanned/materialized. This JIRA focuses on implementing this optimization in the simple case where all scanned columns feed into min/max aggregates and where all columns have parquet::Statistics. Those conditions can be relaxed, but should be addressed separately. This optimization opportunity must be detected by the planner and is not applicable when there are scan predicates. > Use parquet::Statistics for simple min/max aggregates > ----------------------------------------------------- > > Key: IMPALA-5095 > URL: https://issues.apache.org/jira/browse/IMPALA-5095 > Project: IMPALA > Issue Type: Sub-task > Components: Backend > Affects Versions: Impala 2.8.0 > Reporter: Alexander Behm > Labels: parquet, perfomance, ramp-up > > {code} > select min(int_col), max(bigint_col) from parquet_table; > select min(int_col), max(bigint_col) from parquet_table group by partition_col; > select min(int_col), max(int_col) from parquet_table group by partition_col; <--- case a little trickier because int_col refd twice > {code} > The slot values for int_col and bigint_col can be directly filled in from the parquet::Statistics, assuming stats are available for both columns. No columns need to be scanned/materialized. > This JIRA focuses on implementing this optimization in the simple case where all scanned columns feed into min/max aggregates and where all columns have parquet::Statistics. Those conditions can be relaxed, but should be addressed separately. > This optimization opportunity must be detected by the planner and is not applicable when there are scan predicates. -- This message was sent by Atlassian JIRA (v6.3.15#6346)