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 A8EC32009C6 for ; Tue, 31 May 2016 10:43:54 +0200 (CEST) Received: by cust-asf.ponee.io (Postfix) id A6E9C160A23; Tue, 31 May 2016 08:43:54 +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 7F671160A09 for ; Tue, 31 May 2016 10:43:49 +0200 (CEST) Received: (qmail 16880 invoked by uid 500); 31 May 2016 08:43:48 -0000 Mailing-List: contact users-help@asterixdb.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Reply-To: users@asterixdb.apache.org Delivered-To: mailing list users@asterixdb.apache.org Received: (qmail 16870 invoked by uid 99); 31 May 2016 08:43:48 -0000 Received: from pnap-us-west-generic-nat.apache.org (HELO spamd1-us-west.apache.org) (209.188.14.142) by apache.org (qpsmtpd/0.29) with ESMTP; Tue, 31 May 2016 08:43:48 +0000 Received: from localhost (localhost [127.0.0.1]) by spamd1-us-west.apache.org (ASF Mail Server at spamd1-us-west.apache.org) with ESMTP id AFEEFC142B for ; Tue, 31 May 2016 08:43:47 +0000 (UTC) X-Virus-Scanned: Debian amavisd-new at spamd1-us-west.apache.org X-Spam-Flag: NO X-Spam-Score: -0.726 X-Spam-Level: X-Spam-Status: No, score=-0.726 tagged_above=-999 required=6.31 tests=[HTML_MESSAGE=2, KAM_LAZY_DOMAIN_SECURITY=1, RCVD_IN_DNSWL_MED=-2.3, RP_MATCHES_RCVD=-1.426] autolearn=disabled Received: from mx1-lw-us.apache.org ([10.40.0.8]) by localhost (spamd1-us-west.apache.org [10.40.0.7]) (amavisd-new, port 10024) with ESMTP id Tzw4HrSXdNua for ; Tue, 31 May 2016 08:43:45 +0000 (UTC) Received: from hylle05.itea.ntnu.no (hylle05.itea.ntnu.no [129.241.56.225]) by mx1-lw-us.apache.org (ASF Mail Server at mx1-lw-us.apache.org) with ESMTPS id 2481F5F560 for ; Tue, 31 May 2016 08:43:42 +0000 (UTC) Received: from localhost (localhost [127.0.0.1]) by hylle05.itea.ntnu.no (Postfix) with ESMTP id 03A7B907ECB for ; Tue, 31 May 2016 10:43:35 +0200 (CEST) X-Virus-Scanned: Debian amavisd-new at hylle05.itea.ntnu.no Received: from mail-lf0-f43.google.com (mail-lf0-f43.google.com [209.85.215.43]) (using TLSv1.2 with cipher ECDHE-RSA-AES128-GCM-SHA256 (128/128 bits)) (No client certificate requested) (Authenticated sender: kongshem) by hylle05.itea.ntnu.no (Postfix) with ESMTPSA id B7728908152 for ; Tue, 31 May 2016 10:43:32 +0200 (CEST) Received: by mail-lf0-f43.google.com with SMTP id w16so73128900lfd.2 for ; Tue, 31 May 2016 01:43:32 -0700 (PDT) X-Gm-Message-State: ALyK8tKHCqCQXCvsHLQAqI2/ijJ8+3KS4y25I3+X4OTQb5skKpyXfiPnvrALEMNwUjtFMH0B+/e4yCejzl8uGg== X-Received: by 10.25.161.12 with SMTP id k12mr3558285lfe.60.1464684211890; Tue, 31 May 2016 01:43:31 -0700 (PDT) MIME-Version: 1.0 Received: by 10.114.57.228 with HTTP; Tue, 31 May 2016 01:43:11 -0700 (PDT) In-Reply-To: References: From: Magnus Kongshem Date: Tue, 31 May 2016 10:43:11 +0200 X-Gmail-Original-Message-ID: Message-ID: Subject: Re: Indexes not performing well To: users@asterixdb.apache.org Content-Type: multipart/mixed; boundary=001a114038b02b717405341f5e94 archived-at: Tue, 31 May 2016 08:43:54 -0000 --001a114038b02b717405341f5e94 Content-Type: multipart/alternative; boundary=001a114038b02b716d05341f5e92 --001a114038b02b716d05341f5e92 Content-Type: text/plain; charset=UTF-8 On Tue, May 31, 2016 at 6:25 AM, Pouria Pirzadeh wrote: > Hi Magnus, > > Thanks for spending time to gather useful information and sharing them > with us. > No problem, we both benefit from this. > I guess the first potential performance pitfall that you may be falling > into is the large selectivity of the filters you are using against indexed > fields, as Sattam also pointed out. > > 1) With respect to the attached plans to the previous email, did you add > the plans before removing indices or after that ? Because in the plan for > Q2, I can still see that the hour index (which you mentioned you dropped) > is being used at the bottom. > I added the plans before removing the hour and day index. I did however test the queries again, where the result was that the query used the "stamp" index instead and the execution time was still the same. > > 2) If it is not too painful for you, can you also try two sets of > additional queries (their repose time could be helpful): > > - Running a simple count query (without any filter) on the dataset (I > just wanna figure out what is the total time for a pure full scan). > > Sure! The execution time is 267 seconds, interesting result. You will find the optimized logical plan in the attachments. > > - Running those queries that do not benefit from secondary indices > (those with similar times across different versions) without *any* index. > This basically can be done by simply creating a new dataset without any > secondary index, loading your data into it (you can either use bulk load to > load from raw data file(s), OR an "insert into" query to load from your > exiting dataset to the new one) and then running those queries against the > new dataset. I just wanna find out if ignoring all the indices makes a > difference or not. > > I already did this. I created a data set containing the exact same data, but without the indexes. In the pdf excerpt from my thesis, figure 6.5 shows the results. As the figure depicts, the queries do benefit greatly from "ignoring" all indices. I re-attached the pdf in this email. BG, Magnus > > On Mon, May 30, 2016 at 6:08 AM, Magnus Kongshem > wrote: > >> Attached you will find: >> >> - My DLL >> - My queries and their optimized logical plan >> >> From what I can interpret, the queries does not use any of the combined >> indexes. And query number two, three and four uses the "hour" index which >> is based on the hourOfDay field. As Sattam states, indexes based on this >> field may not be optimal. I deleted that index as well as the "day" index >> and re-ran the queries. The result was that the queries used the "stamp" >> index instead with the same poor execution time. >> >> I'm having some trouble creating a dataset with a filter. I keep getting: >> >> type mismatch: missing a required closed field uid:uuid [IllegalStateException] >> >> use dataverse bigd; >> >> create type table2 as closed { >> uid: uuid, >> campus: string, >> building: string, >> floor: string, >> timestamp: int32, >> dayOfWeek: int32, >> hourOfDay: int32, >> latitude: double, >> salt_timestamp: int32, >> longitude: double, >> id: string, >> accuracy: double >> } >> create dataset posdata3(table2) >> primary key uid autogenerated with filter on timestamp; >> >> load dataset posdata3 using localfs >> (("path"="path/to/file/all.adm"),("format"="adm")); >> >> BG, >> Magnus >> >> On Mon, May 30, 2016 at 10:01 AM, Magnus Kongshem >> wrote: >> >>> Thank you for your replies. I will test your thoughts by dropping the >>> hourOfDay and dayOfWeek indexes, send you the optimized query plans and >>> utilize the AsterixDB filters. >>> >>> I'll be back. >>> >>> BG, >>> Magnus >>> >>> On Sun, May 29, 2016 at 8:32 AM, Sattam Alsubaiee >>> wrote: >>> >>>> Creating indexes on fields with high selectivities (such as hourOfDay >>>> and dayOfWeek) are not encouraged at all. Each secondary index lookup will >>>> have to probe the primary index to fetch other fields in the record. It >>>> would be much more efficient if you just perform scans as opposed of >>>> accessing secondary indexes when querying such fields. >>>> >>>> I would recommend that you drop at least the following indexes: >>>> drop index posdata.hour; >>>> drop index posdata.day; >>>> >>>> Also I would highly recommend that you utilize AsterixDB filters, which >>>> is very good optimization (could save up to 99% of query time) when you >>>> deal with time-correlated fields such as timestamps: >>>> https://asterixdb.apache.org/docs/0.8.8-incubating/aql/filters.html >>>> http://dl.acm.org/citation.cfm?id=2786007 >>>> >>>> Cheers, >>>> Sattam >>>> >>>> On Sun, May 29, 2016 at 8:58 AM, Michael Carey >>>> wrote: >>>> >>>>> @Pouria: Please share your findings here when you check this out - >>>>> this is quite strange, since none of the other performance results that >>>>> have been obtained on the system have looked anything like this. (I will >>>>> try to look at this too at some point, but will unfortunately be MIA from >>>>> June 1-15 first.) Weird.... >>>>> >>>>> On 5/26/16 9:20 AM, Pouria Pirzadeh wrote: >>>>> >>>>> Hi Magnus, >>>>> >>>>> Thanks for your email and sharing the information. >>>>> If it is Ok with you, Would you please share with us the exact DDL >>>>> (including type definitions, dataset and index definitions) and exact AQL >>>>> queries that you ran against AsterixDB ? >>>>> I am just interested in checking the query plans and see what ended up >>>>> being run as jobs. >>>>> >>>>> Thanks. >>>>> Pouria >>>>> >>>>> On Thu, May 26, 2016 at 4:59 AM, Magnus Kongshem < >>>>> kongshem@online.ntnu.no> wrote: >>>>> >>>>>> Hi, >>>>>> >>>>>> There has been a lot of questions from me regarding AsterixDB and I >>>>>> thank all of you who have answered me. So it is time for me to contribute >>>>>> with some obeservations. I am writing my master thesis where I test >>>>>> multiple databases on a large data set. I should also mention that I have >>>>>> installed AsterixDB on a single machine. >>>>>> >>>>>> What I have observed is that asterixDB has a "poorer" read >>>>>> performance when I specify indexes on the data set compared to not >>>>>> implementing any indexes. See the attachment for details, its an excerpt of >>>>>> my thesis explaining and describing the queries, the indexes and the test >>>>>> results. Any thoughts on these test results? >>>>>> >>>>>> I also cannot help to notice that the read performance for a query >>>>>> querying a small portion, medium portion and large portion of the data set >>>>>> is very similar. The largest query finds 75 million records and the >>>>>> smallest query finds 3.5 million records, but almost have the same read >>>>>> performance. How can this be? >>>>>> >>>>>> Perhaps you can use these test results in the future development of >>>>>> asterixDB. >>>>>> >>>>>> I you would like, I can send you my final thesis when it's done. >>>>>> >>>>>> -- >>>>>> >>>>>> Mvh >>>>>> >>>>>> Magnus Alderslyst Kongshem >>>>>> +47 415 65 906 <%2B47%20415%2065%20906> >>>>>> >>>>> >>>>> --001a114038b02b716d05341f5e92 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable


On Tue, May 31, 2016 at 6:25 AM, Pouria Pirzadeh <= pouria.pirza= deh@gmail.com> wrote:
Hi= Magnus,

Thanks for spending time to gather useful infor= mation and sharing them with us.
No problem, w= e both benefit from this.
=C2=A0
I guess the first potential performance pitfall that you may = be falling into is the large selectivity of the filters you are using again= st indexed fields, as Sattam also pointed out.=C2=A0

1) With respect to the attached plans to the previous email, did you add= the plans before removing indices or after that ? Because in the plan for = Q2, I can still see that the hour index (which you mentioned you dropped) i= s being used at the bottom.
I added the plans = before removing the hour and day index. I did however test the queries agai= n, where the result was that the query used the "stamp" index ins= tead and the execution time was still the same.=C2=A0

2) If it is not too painful for you, = can you also try two sets of additional queries (their repose time could be= helpful):
  • Running a simple count query (without any filt= er) on the dataset (I just wanna figure out what is the total time for a pu= re full scan).
=C2=A0Sure! The e= xecution time is 267 seconds, interesting result. You will find the optimiz= ed logical plan in the attachments.=C2=A0
  • Running those queries that do not benefit from secondary= indices (those with similar times across different versions) without *any*= index. This basically can be done by simply creating a new dataset without= any secondary index, loading your data into it (you can either use bulk lo= ad to load from raw data file(s), OR an "insert into" query to lo= ad from your exiting dataset to the new one) and then running those queries= against the new dataset. I just wanna find out if ignoring all the indices= makes a difference or not.
=C2=A0I = already did this. I created a data set containing the exact same data, but = without the indexes. In the pdf excerpt from my thesis, figure 6.5 shows th= e results. As the figure depicts, the queries do benefit greatly from "= ;ignoring" all indices. I re-attached the pdf in this email.

BG,

Magnus
=C2=A0

On Mon, May 30, 2016 at 6:08 AM, Magnus Kongshem <kon= gshem@stud.ntnu.no> wrote:
Attached you will find:

- My DLL
- My queries and thei= r optimized logical plan

From what I can interpret= , the queries does not use any of the combined indexes. And query number tw= o, three and four uses the "hour" index which is based on the hou= rOfDay field. As Sattam states, indexes based on this field may not be opti= mal. I deleted that index as well as the "day" index and re-ran t= he queries. The result was that the queries used the "stamp" inde= x instead with the same poor execution time.

I'= ;m having some trouble creating a dataset with a filter. I keep getting:=C2= =A0
type mi=
smatch: missing a required closed field uid:uuid [IllegalStateException]
use dataverse bigd;

=C2=A0 =C2= =A0 create type table2 as closed {
uid: uuid,
=C2=A0 =C2=A0 =C2=A0 =C2=A0 campu= s: string,
building:= string,
floor: stri= ng,
=C2=A0 =C2=A0 =C2=A0 =C2=A0 timestamp: int32,
dayOfWeek: int32,
hourOfDay: int32,
=C2=A0 = =C2=A0 =C2=A0 =C2=A0 latitude: double,
=C2=A0 =C2=A0 =C2=A0 =C2= =A0 salt_timestamp: int32,
=C2=A0 =C2=A0 =C2=A0 =C2=A0 longitude:= double,
=C2=A0 =C2=A0 =C2=A0 =C2=A0 id: string,
accuracy: double
=C2=A0 = =C2=A0 }
create dataset posdata3(table2)=C2=A0
p= rimary key uid autogenerated with filter on timestamp;

=
load dataset posdata3 using localfs (("path"=3D"path/to= /file/all.adm"),("format"=3D"adm"));

BG,
Magnus

On Mon, May 30, 2016 at 10:01 AM,= Magnus Kongshem <kongshem@stud.ntnu.no> wrote:
Thank you for your replies. I will test your t= houghts by dropping the hourOfDay and dayOfWeek indexes, send you the optim= ized query plans and utilize the AsterixDB filters.

I= 9;ll be back.

BG,
Magnus

On Sun, May 29, 2= 016 at 8:32 AM, Sattam Alsubaiee <salsubaiee@gmail.com> w= rote:
Creating indexes on fields with = high selectivities (such as=C2=A0hourOfDay= and=C2=A0dayOfWeek) are not=C2=A0encouraged=C2=A0at all. Each secondary in= dex lookup will have to probe the primary index to fetch other fields in th= e record. It would be much more=C2=A0efficient=C2=A0if you just perform sca= ns as opposed of accessing secondary indexes when querying such fields.

I would recommend that you drop at least the foll= owing indexes:
drop = index posdata.hour;
d= rop index posdata.day;

Also I would highly recommend= that you utilize AsterixDB filters, which is very good optimization (could= save up to 99% of query time) when you deal with time-correlated fields su= ch as timestamps:

Cheers,
Sattam

=
On Sun, May 29, 2016 at 8:58 AM, Michael Carey <= span dir=3D"ltr"><mjcarey@ics.uci.edu> wrote:
=20 =20 =20

@Pouria: Please share your findings here when you check this out - this is quite strange, since none of the other performance results that have been obtained on the system have looked anything like this.=C2=A0 (I will try to look at this too at some point, but will unfortunately be MIA from June 1-15 first.)=C2=A0 Weird....


On 5/26/16 9:20 AM, Pouria Pirzadeh wrote:
Hi Magnus,

Thanks for your email and sharing the information.
If it is Ok with you, Would you please share with us the exact DDL (including type definitions, dataset and index definitions) and exact AQL queries that you ran against AsterixDB ?
I am just interested in checking the query plans and see what ended up being run as jobs.

Thanks.
Pouria

On Thu, May 26, 2016 at 4:59 AM, Magnus Kongshem <kongshem@online.ntnu.no> wrote:
Hi,

There has been a lot of questions from me regarding AsterixDB and I thank all of you who have answered me. So it is time for me to contribute with some obeservations. I am writing my master thesis where I test multiple databases on a large data set. I should also mention that I have installed AsterixDB on a single machine.=C2=A0

What I have observed is that asterixDB has a "poore= r" read performance when I specify indexes on the data set compared to not implementing any indexes. See the attachment for details, its an excerpt of my thesis explaining and describing the queries, the indexes and the test results. Any thoughts on these test results?

I also cannot help to notice that the read performance for a query querying a small portion, medium portion and large portion of the data set is very similar. The largest query finds 75 million records and the smallest query finds 3.5 million records, but almost have the same read performance. How can this be?

Perhaps you can use these test results in the future development of asterixDB.=C2=A0

I you would like, I can send you my final thesis when it's done.=C2=A0

--

Mvh

Magnus Alderslyst Kongshem
+47 415 65 906



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