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 252F618086 for ; Mon, 19 Oct 2015 11:15:44 +0000 (UTC) Received: (qmail 56607 invoked by uid 500); 19 Oct 2015 11:00:44 -0000 Delivered-To: apmail-spark-user-archive@spark.apache.org Received: (qmail 56541 invoked by uid 500); 19 Oct 2015 11:00:43 -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 56531 invoked by uid 99); 19 Oct 2015 11:00:43 -0000 Received: from Unknown (HELO spamd3-us-west.apache.org) (209.188.14.142) by apache.org (qpsmtpd/0.29) with ESMTP; Mon, 19 Oct 2015 11:00:43 +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 E3EFC180DD9 for ; Mon, 19 Oct 2015 11:00:41 +0000 (UTC) X-Virus-Scanned: Debian amavisd-new at spamd3-us-west.apache.org X-Spam-Flag: NO X-Spam-Score: 4.213 X-Spam-Level: **** X-Spam-Status: No, score=4.213 tagged_above=-999 required=6.31 tests=[DKIM_SIGNED=0.1, DKIM_VALID=-0.1, DKIM_VALID_AU=-0.1, HTML_MESSAGE=3, SPF_PASS=-0.001, URIBL_BLOCKED=0.001, URI_HEX=1.313] autolearn=disabled Authentication-Results: spamd3-us-west.apache.org (amavisd-new); dkim=pass (2048-bit key) header.d=gmail.com Received: from mx1-eu-west.apache.org ([10.40.0.8]) by localhost (spamd3-us-west.apache.org [10.40.0.10]) (amavisd-new, port 10024) with ESMTP id CuAkCloPKR-t for ; Mon, 19 Oct 2015 11:00:30 +0000 (UTC) Received: from mail-ob0-f170.google.com (mail-ob0-f170.google.com [209.85.214.170]) by mx1-eu-west.apache.org (ASF Mail Server at mx1-eu-west.apache.org) with ESMTPS id 091FA20F7B for ; Mon, 19 Oct 2015 11:00:28 +0000 (UTC) Received: by obbzf10 with SMTP id zf10so135211396obb.2 for ; Mon, 19 Oct 2015 04:00:26 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=gmail.com; s=20120113; h=mime-version:in-reply-to:references:date:message-id:subject:from:to :cc:content-type; bh=JdZ5JeQqQbXocWZE0YHHdXzQe8ZmqjCJ67Bg4FtO4kM=; b=Pt0bYcVi3yWkfn9UqKPVJZGHxfkMYCi46tVcMnB1oakjqhGjPKT53CT5dlsLVlurR8 qlYs294JUaGWiS0hCeZKBDhc6gh2JISe6kPJoutebq9600j0rnUZpCX1mrPLv5WvpkIj wVdKW5ZWfV/c/cDcV/xrCDJ/1zKtgzo2sowsIs+j4xoBKOmBgXD0b+bO4vL3BOVOGciW MVHBTRRi+6HQxtNrUWfKLE9i2PLsL28pNgORLZlYMYlhhzRUcHzgTN8OtoTnucH7yVJD kxb63fMHamZVvuaTIEdOrQpD/ww3n2wcmu0E09v6bFImyUUNlTi7E7mQrIBVN9tGHjfy pxNg== MIME-Version: 1.0 X-Received: by 10.60.47.199 with SMTP id f7mr17413073oen.54.1445252426653; Mon, 19 Oct 2015 04:00:26 -0700 (PDT) Received: by 10.202.79.131 with HTTP; Mon, 19 Oct 2015 04:00:25 -0700 (PDT) Received: by 10.202.79.131 with HTTP; Mon, 19 Oct 2015 04:00:25 -0700 (PDT) In-Reply-To: References: <1445152244061-25111.post@n3.nabble.com> Date: Mon, 19 Oct 2015 16:30:25 +0530 Message-ID: Subject: Re: callUdf("percentile_approx",col("mycol"),lit(0.25)) does not compile spark 1.5.1 source but it does work in spark 1.5.1 bin From: Umesh Kacha To: Ted Yu Cc: user Content-Type: multipart/mixed; boundary=001a11c358de8066680522730d4a --001a11c358de8066680522730d4a Content-Type: multipart/alternative; boundary=001a11c358de8066640522730d48 --001a11c358de8066640522730d48 Content-Type: text/plain; charset=UTF-8 Hi Ted thanks much for your help really appreciate it. I tried to use maven dependencies you mentioned but still callUdf is not compiling please find snap shot of my intellij editor. I am sorry you may have to zoom pictures as I can't share code. Thanks again. On Oct 19, 2015 8:32 AM, "Ted Yu" wrote: > Umesh: > > $ jar tvf > /home/hbase/.m2/repository/org/spark-project/hive/hive-exec/1.2.1.spark/hive-exec-1.2.1.spark.jar > | grep GenericUDAFPercentile > 2143 Fri Jul 31 23:51:48 PDT 2015 > org/apache/hadoop/hive/ql/udf/generic/GenericUDAFPercentileApprox$1.class > 4602 Fri Jul 31 23:51:48 PDT 2015 > org/apache/hadoop/hive/ql/udf/generic/GenericUDAFPercentileApprox$GenericUDAFMultiplePercentileApproxEvaluator.class > > As long as the following dependency is in your pom.xml: > [INFO] +- org.spark-project.hive:hive-exec:jar:1.2.1.spark:compile > > You should be able to invoke percentile_approx > > Cheers > > On Sun, Oct 18, 2015 at 8:58 AM, Umesh Kacha > wrote: > >> Thanks much Ted so when do we get to use this sparkUdf in Java code using >> maven code dependencies?? You said JIRA 10671 is not pushed as part of >> 1.5.1 so it should be released in 1.6.0 as mentioned in the JIRA right? >> >> On Sun, Oct 18, 2015 at 9:20 PM, Ted Yu wrote: >> >>> The udf is defined in GenericUDAFPercentileApprox of hive. >>> >>> When spark-shell runs, it has access to the above class which is >>> packaged >>> in assembly/target/scala-2.10/spark-assembly-1.6.0-SNAPSHOT-hadoop2.7.0.jar >>> : >>> >>> 2143 Fri Oct 16 15:02:26 PDT 2015 >>> org/apache/hadoop/hive/ql/udf/generic/GenericUDAFPercentileApprox$1.class >>> 4602 Fri Oct 16 15:02:26 PDT 2015 >>> org/apache/hadoop/hive/ql/udf/generic/GenericUDAFPercentileApprox$GenericUDAFMultiplePercentileApproxEvaluator.class >>> 1697 Fri Oct 16 15:02:26 PDT 2015 >>> org/apache/hadoop/hive/ql/udf/generic/GenericUDAFPercentileApprox$GenericUDAFPercentileApproxEvaluator$PercentileAggBuf.class >>> 6570 Fri Oct 16 15:02:26 PDT 2015 >>> org/apache/hadoop/hive/ql/udf/generic/GenericUDAFPercentileApprox$GenericUDAFPercentileApproxEvaluator.class >>> 4334 Fri Oct 16 15:02:26 PDT 2015 >>> org/apache/hadoop/hive/ql/udf/generic/GenericUDAFPercentileApprox$GenericUDAFSinglePercentileApproxEvaluator.class >>> 6293 Fri Oct 16 15:02:26 PDT 2015 >>> org/apache/hadoop/hive/ql/udf/generic/GenericUDAFPercentileApprox.class >>> >>> That was the cause for different behavior. >>> >>> FYI >>> >>> On Sun, Oct 18, 2015 at 12:10 AM, unk1102 wrote: >>> >>>> Hi starting new thread following old thread looks like code for >>>> compiling >>>> callUdf("percentile_approx",col("mycol"),lit(0.25)) is not merged in >>>> spark >>>> 1.5.1 source but I dont understand why this function call works in Spark >>>> 1.5.1 spark-shell/bin. Please guide. >>>> >>>> ---------- Forwarded message ---------- >>>> From: "Ted Yu" >>>> Date: Oct 14, 2015 3:26 AM >>>> Subject: Re: How to calculate percentile of a column of DataFrame? >>>> To: "Umesh Kacha" >>>> Cc: "Michael Armbrust" , >>>> "<Saif.A.Ellafi@wellsfargo.com>" , >>>> "user" >>>> >>>> I modified DataFrameSuite, in master branch, to call percentile_approx >>>> instead of simpleUDF : >>>> >>>> - deprecated callUdf in SQLContext >>>> - callUDF in SQLContext *** FAILED *** >>>> org.apache.spark.sql.AnalysisException: undefined function >>>> percentile_approx; >>>> at >>>> >>>> org.apache.spark.sql.catalyst.analysis.SimpleFunctionRegistry$$anonfun$2.apply(FunctionRegistry.scala:64) >>>> at >>>> >>>> org.apache.spark.sql.catalyst.analysis.SimpleFunctionRegistry$$anonfun$2.apply(FunctionRegistry.scala:64) >>>> at scala.Option.getOrElse(Option.scala:120) >>>> at >>>> >>>> org.apache.spark.sql.catalyst.analysis.SimpleFunctionRegistry.lookupFunction(FunctionRegistry.scala:63) >>>> at >>>> >>>> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$10$$anonfun$applyOrElse$5$$anonfun$applyOrElse$24.apply(Analyzer.scala:506) >>>> at >>>> >>>> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$10$$anonfun$applyOrElse$5$$anonfun$applyOrElse$24.apply(Analyzer.scala:506) >>>> at >>>> >>>> org.apache.spark.sql.catalyst.analysis.package$.withPosition(package.scala:48) >>>> at >>>> >>>> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$10$$anonfun$applyOrElse$5.applyOrElse(Analyzer.scala:505) >>>> at >>>> >>>> org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$apply$10$$anonfun$applyOrElse$5.applyOrElse(Analyzer.scala:502) >>>> at >>>> >>>> org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scala:227) >>>> >>>> SPARK-10671 is included. >>>> For 1.5.1, I guess the absence of SPARK-10671 means that SparkSQL treats >>>> percentile_approx as normal UDF. >>>> >>>> Experts can correct me, if there is any misunderstanding. >>>> >>>> Cheers >>>> >>>> >>>> >>>> -- >>>> View this message in context: >>>> http://apache-spark-user-list.1001560.n3.nabble.com/callUdf-percentile-approx-col-mycol-lit-0-25-does-not-compile-spark-1-5-1-source-but-it-does-work-inn-tp25111.html >>>> Sent from the Apache Spark User List mailing list archive at Nabble.com. >>>> >>>> --------------------------------------------------------------------- >>>> To unsubscribe, e-mail: user-unsubscribe@spark.apache.org >>>> For additional commands, e-mail: user-help@spark.apache.org >>>> >>>> >>> >> > --001a11c358de8066640522730d48 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable

Hi Ted thanks much for your help really appreciate it. I tri= ed to use maven dependencies you mentioned but still callUdf is not compili= ng please find snap shot of my intellij editor. I am sorry you may have to = zoom pictures as I can't share code. Thanks again.

On Oct 19, 2015 8:32 AM, "Ted Yu" <= yuzhihong@gmail.com> wrote:
Umesh:

$ jar tvf /home/hbase/.m2/repository/org/s= park-project/hive/hive-exec/1.2.1.spark/hive-exec-1.2.1.spark.jar | grep Ge= nericUDAFPercentile
=C2=A0 2143 Fri Jul 31 23:51:48 PDT 2015 org/= apache/hadoop/hive/ql/udf/generic/GenericUDAFPercentileApprox$1.class
=
=C2=A0 4602 Fri Jul 31 23:51:48 PDT 2015 org/apache/hadoop/hive/ql/udf= /generic/GenericUDAFPercentileApprox$GenericUDAFMultiplePercentileApproxEva= luator.class

As long as the following dependency i= s in your pom.xml:
[INFO] +- org.spark-project.hive:hive-exec:jar= :1.2.1.spark:compile

You should be able to inv= oke=C2=A0percentile_approx

Cheers

On Sun, Oct 18, 2015 a= t 8:58 AM, Umesh Kacha <umesh.kacha@gmail.com> wrote:
Thanks much Ted so when do= we get to use this sparkUdf in Java code using maven code dependencies?? Y= ou said JIRA=C2=A010671=C2=A0is not= pushed as part of 1.5.1 so it should be released in 1.6.0 as mentioned in = the JIRA right?

On Sun, Oct 18, 2015 at 9:20 PM, Ted Yu <= ;yuzhihong@gmail.c= om> wrote:
The udf is defined in=C2=A0GenericUDAFPercentileApprox of hive.

When spark-shell runs, it has access to the above class which is p= ackaged in=C2=A0assembly/target/scala-2.10/spark-assembly-1.6.0-SNAPSHOT-ha= doop2.7.0.jar :

=C2=A0 2143 Fri Oct 16 15:02:= 26 PDT 2015 org/apache/hadoop/hive/ql/udf/generic/GenericUDAFPercentileAppr= ox$1.class
=C2=A0 4602 Fri Oct 16 15:02:26 PDT 2015 org/apache/ha= doop/hive/ql/udf/generic/GenericUDAFPercentileApprox$GenericUDAFMultiplePer= centileApproxEvaluator.class
=C2=A0 1697 Fri Oct 16 15:02:26 PDT = 2015 org/apache/hadoop/hive/ql/udf/generic/GenericUDAFPercentileApprox$Gene= ricUDAFPercentileApproxEvaluator$PercentileAggBuf.class
=C2=A0 65= 70 Fri Oct 16 15:02:26 PDT 2015 org/apache/hadoop/hive/ql/udf/generic/Gener= icUDAFPercentileApprox$GenericUDAFPercentileApproxEvaluator.class
=C2=A0 4334 Fri Oct 16 15:02:26 PDT 2015 org/apache/hadoop/hive/ql/udf/gen= eric/GenericUDAFPercentileApprox$GenericUDAFSinglePercentileApproxEvaluator= .class
=C2=A0 6293 Fri Oct 16 15:02:26 PDT 2015 org/apache/hadoop= /hive/ql/udf/generic/GenericUDAFPercentileApprox.class

=
That was the cause for different behavior.

<= div>FYI

On Sun, Oct 18, 2015 at 12:10 AM, unk1102 <umesh.kacha@gmail.com> wrote:
Hi starting new thre= ad following old thread looks like code for compiling
callUdf("percentile_approx",col("mycol"),lit(0.25)) is = not merged in spark
1.5.1 source but I dont understand why this function call works in Spark 1.5.1 spark-shell/bin. Please guide.

---------- Forwarded message ----------
From: "Ted Yu" <yuzhihong@gmail.com>
Date: Oct 14, 2015 3:26 AM
Subject: Re: How to calculate percentile of a column of DataFrame?
To: "Umesh Kacha" <umesh.kacha@gmail.com>
Cc: "Michael Armbrust" <michael@databricks.com>,
"&lt;Saif.A.Ellafi@wellsfargo.com&gt;" <Saif.A.Ellafi@wellsfarg= o.com>,
"user" <user@spark.apache.org>

I modified DataFrameSuite, in master branch, to call percentile_approx
instead of simpleUDF :

- deprecated callUdf in SQLContext
- callUDF in SQLContext *** FAILED ***
=C2=A0 org.apache.spark.sql.AnalysisException: undefined function
percentile_approx;
=C2=A0 at
org.apache.spark.sql.catalyst.analysis.SimpleFunctionRegistry$$anonfun$2.ap= ply(FunctionRegistry.scala:64)
=C2=A0 at
org.apache.spark.sql.catalyst.analysis.SimpleFunctionRegistry$$anonfun$2.ap= ply(FunctionRegistry.scala:64)
=C2=A0 at scala.Option.getOrElse(Option.scala:120)
=C2=A0 at
org.apache.spark.sql.catalyst.analysis.SimpleFunctionRegistry.lookupFunctio= n(FunctionRegistry.scala:63)
=C2=A0 at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$a= pply$10$$anonfun$applyOrElse$5$$anonfun$applyOrElse$24.apply(Analyzer.scala= :506)
=C2=A0 at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$a= pply$10$$anonfun$applyOrElse$5$$anonfun$applyOrElse$24.apply(Analyzer.scala= :506)
=C2=A0 at
org.apache.spark.sql.catalyst.analysis.package$.withPosition(package.scala:= 48)
=C2=A0 at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$a= pply$10$$anonfun$applyOrElse$5.applyOrElse(Analyzer.scala:505)
=C2=A0 at
org.apache.spark.sql.catalyst.analysis.Analyzer$ResolveFunctions$$anonfun$a= pply$10$$anonfun$applyOrElse$5.applyOrElse(Analyzer.scala:502)
=C2=A0 at
org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$3.apply(TreeNode.scal= a:227)

SPARK-10671 is included.
For 1.5.1, I guess the absence of SPARK-10671 means that SparkSQL treats percentile_approx as normal UDF.

Experts can correct me, if there is any misunderstanding.

Cheers



--
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AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAA --001a11c358de8066680522730d4a Content-Type: text/plain; charset=us-ascii --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscribe@spark.apache.org For additional commands, e-mail: user-help@spark.apache.org --001a11c358de8066680522730d4a--