RE: Query 3x slower with index

2018-10-12 Thread Stanislav Lukyanov
Yes, sure. 

From: Dave Harvey
Sent: 11 октября 2018 г. 23:59
To: user@ignite.apache.org
Subject: Re: Query 3x slower with index

"Ignite will only use one index per table"

I assume you mean "Ignite will only use one index per table per query"?

On Thu, Oct 11, 2018 at 1:55 PM Stanislav Lukyanov  
wrote:
Hi,
 
It is a rather lengthy thread and I can’t dive into details right now, 
but AFAICS the issue now is making affinity key index to work with a secondary 
index.
The important things to understand is
1. Ignite will only use one index per table
2. In case of a composite index, it will apply the columns one by one
3. The affinity key index should always go first as the first step is splitting 
the query by affinity key values
 
So, to use index over the affinity key (customer_id) and a secondary index 
(category_id) one needs to create an index 
like (customer_id, category_id), in that order, with no columns in between.
Note that index (customer_id, dt, category_id) can’t be used instead of it.
On the other hand, (customer_id, category_id, dt) can - the last part of the 
index will be left unused.
 
Thanks,
Stan
 
From: eugene miretsky
Sent: 9 октября 2018 г. 19:40
To: user@ignite.apache.org
Subject: Re: Query 3x slower with index
 
Hi Ilya, 
 
I have tried it, and got the same performance as forcing using category index 
in my initial benchmark - query is 3x slowers and uses only one thread. 
 
From my experiments so far it seems like Ignite can either (a) use affinity key 
and run queries in parallel, (b) use index but run the query on only one 
thread. 
 
Has anybody been able to run OLAP like queries in while using an index? 
 
Cheers,
Eugene
 
On Mon, Sep 24, 2018 at 10:55 AM Ilya Kasnacheev  
wrote:
Hello!
 
I guess that using AFFINITY_KEY as index have something to do with the fact 
that GROUP BY really wants to work per-partition.
 
I have the following query for you:
 
1: jdbc:ignite:thin://localhost> explain Select count(*) FROM( Select 
customer_id from (Select customer_id, product_views_app, product_clict_app from 
GA_DATA ga join table(category_id int = ( 117930, 175930, 
175940,175945,101450)) cats on cats.category_id = ga.category_id) data group by 
customer_id having SUM(product_views_app) > 2 OR  SUM(product_clict_app) > 1);
PLAN  SELECT
    DATA__Z2.CUSTOMER_ID AS __C0_0,
    SUM(DATA__Z2.PRODUCT_VIEWS_APP) AS __C0_1,
    SUM(DATA__Z2.PRODUCT_CLICT_APP) AS __C0_2
FROM (
    SELECT
    GA__Z0.CUSTOMER_ID,
    GA__Z0.PRODUCT_VIEWS_APP,
    GA__Z0.PRODUCT_CLICT_APP
    FROM TABLE(CATEGORY_ID INTEGER=(117930, 175930, 175940, 175945, 101450)) 
CATS__Z1
    INNER JOIN PUBLIC.GA_DATA GA__Z0
    ON 1=1
    WHERE CATS__Z1.CATEGORY_ID = GA__Z0.CATEGORY_ID
) DATA__Z2
    /* SELECT
    GA__Z0.CUSTOMER_ID,
    GA__Z0.PRODUCT_VIEWS_APP,
    GA__Z0.PRODUCT_CLICT_APP
    FROM TABLE(CATEGORY_ID INTEGER=(117930, 175930, 175940, 175945, 101450)) 
CATS__Z1
    /++ function ++/
    INNER JOIN PUBLIC.GA_DATA GA__Z0
    /++ PUBLIC.GA_CATEGORY_ID: CATEGORY_ID = CATS__Z1.CATEGORY_ID ++/
    ON 1=1
    WHERE CATS__Z1.CATEGORY_ID = GA__Z0.CATEGORY_ID
 */
GROUP BY DATA__Z2.CUSTOMER_ID

PLAN  SELECT
    COUNT(*)
FROM (
    SELECT
    __C0_0 AS CUSTOMER_ID
    FROM PUBLIC.__T0
    GROUP BY __C0_0
    HAVING (SUM(__C0_1) > 2)
    OR (SUM(__C0_2) > 1)
) _18__Z3
    /* SELECT
    __C0_0 AS CUSTOMER_ID
    FROM PUBLIC.__T0
    /++ PUBLIC."merge_scan" ++/
    GROUP BY __C0_0
    HAVING (SUM(__C0_1) > 2)
    OR (SUM(__C0_2) > 1)
 */
 
However, I'm not sure it is "optimal" or not since I have no idea if it will 
perform better or worse on real data. That's why I need a subset of data which 
will make query execution speed readily visible. Unfortunately, I can't deduce 
that from query plan alone.
 
Regards,
-- 
Ilya Kasnacheev
 
 
пн, 24 сент. 2018 г. в 16:14, eugene miretsky :
An easy way to reproduce would be to 
 
1. Create table
CREATE TABLE GA_DATA (
    customer_id bigint,
    dt timestamp,
    category_id int,
    product_views_app int,
    product_clict_app int,
    product_clict_web int,
    product_clict_web int,
    PRIMARY KEY (customer_id, dt, category_id)
) WITH "template=ga_template, backups=0, affinityKey=customer_id";
 
2. Create indexes
• CREATE INDEX ga_customer_id ON GA_Data (customer_id)
• CREATE INDEX ga_pKey ON GA_Data (customer_id, dt, category_id)
• CREATE INDEX ga_category_and_customer_id ON GA_Data (category_id, 
customer_id)
• CREATE INDEX ga_category_id ON GA_Data (category_id)
3. Run Explain on the following queries while trying forcing using different 
indexes
• Select count(*) FROM( 
Select customer_id from GA_DATA  use index (ga_category_id)
where category_id in (117930, 175930, 175940,175945,101450) 
group by customer_id having SUM(product_views_app) > 2 OR  
SUM(product_clicks_app) > 1 )
 
• Sel

Re: Query 3x slower with index

2018-10-12 Thread wt
having worked with databases for 20 years i can see your indexes are not
fully scoped. i see this as your issue

having SUM(product_views_app) > 2 OR  SUM(product_clicks_app) > 1

add those columns to the composite index so that it doesn't need to access
the underlying table and can just use the index.



--
Sent from: http://apache-ignite-users.70518.x6.nabble.com/


Re: Query 3x slower with index

2018-10-11 Thread Dave Harvey
"Ignite will only use one index per table"

I assume you mean "Ignite will only use one index per table per query"?

On Thu, Oct 11, 2018 at 1:55 PM Stanislav Lukyanov 
wrote:

> Hi,
>
>
>
> It is a rather lengthy thread and I can’t dive into details right now,
>
> but AFAICS the issue now is making affinity key index to work with a
> secondary index.
>
> The important things to understand is
>
>1. Ignite will only use one index per table
>2. In case of a composite index, it will apply the columns one by one
>3. The affinity key index should always go first as the first step is
>splitting the query by affinity key values
>
>
>
> So, to use index over the affinity key (customer_id) and a secondary index
> (category_id) one needs to create an index
>
> like (customer_id, category_id), in that order, with no columns in between.
>
> Note that index (customer_id, dt, category_id) can’t be used instead of it.
>
> On the other hand, (customer_id, category_id, dt) can - the last part of
> the index will be left unused.
>
>
>
> Thanks,
>
> Stan
>
>
>
> *From: *eugene miretsky 
> *Sent: *9 октября 2018 г. 19:40
> *To: *user@ignite.apache.org
> *Subject: *Re: Query 3x slower with index
>
>
>
> Hi Ilya,
>
>
>
> I have tried it, and got the same performance as forcing using category
> index in my initial benchmark - query is 3x slowers and uses only one
> thread.
>
>
>
> From my experiments so far it seems like Ignite can either (a) use
> affinity key and run queries in parallel, (b) use index but run the query
> on only one thread.
>
>
>
> Has anybody been able to run OLAP like queries in while using an index?
>
>
>
> Cheers,
>
> Eugene
>
>
>
> On Mon, Sep 24, 2018 at 10:55 AM Ilya Kasnacheev <
> ilya.kasnach...@gmail.com> wrote:
>
> Hello!
>
>
>
> I guess that using AFFINITY_KEY as index have something to do with the
> fact that GROUP BY really wants to work per-partition.
>
>
>
> I have the following query for you:
>
>
>
> 1: jdbc:ignite:thin://localhost> explain Select count(*) FROM( Select
> customer_id from (Select customer_id, product_views_app, product_clict_app
> from GA_DATA ga join table(category_id int = ( 117930, 175930,
> 175940,175945,101450)) cats on cats.category_id = ga.category_id) data
> group by customer_id having SUM(product_views_app) > 2 OR
> SUM(product_clict_app) > 1);
> PLAN  SELECT
> DATA__Z2.CUSTOMER_ID AS __C0_0,
> SUM(DATA__Z2.PRODUCT_VIEWS_APP) AS __C0_1,
> SUM(DATA__Z2.PRODUCT_CLICT_APP) AS __C0_2
> FROM (
> SELECT
> GA__Z0.CUSTOMER_ID,
> GA__Z0.PRODUCT_VIEWS_APP,
> GA__Z0.PRODUCT_CLICT_APP
> FROM TABLE(CATEGORY_ID INTEGER=(117930, 175930, 175940, 175945,
> 101450)) CATS__Z1
> INNER JOIN PUBLIC.GA_DATA GA__Z0
> ON 1=1
> WHERE CATS__Z1.CATEGORY_ID = GA__Z0.CATEGORY_ID
> ) DATA__Z2
> /* SELECT
> GA__Z0.CUSTOMER_ID,
> GA__Z0.PRODUCT_VIEWS_APP,
> GA__Z0.PRODUCT_CLICT_APP
> FROM TABLE(CATEGORY_ID INTEGER=(117930, 175930, 175940, 175945,
> 101450)) CATS__Z1
> /++ function ++/
> INNER JOIN PUBLIC.GA_DATA GA__Z0
> /++ PUBLIC.GA_CATEGORY_ID: CATEGORY_ID = CATS__Z1.CATEGORY_ID ++/
> ON 1=1
> WHERE CATS__Z1.CATEGORY_ID = GA__Z0.CATEGORY_ID
>  */
> GROUP BY DATA__Z2.CUSTOMER_ID
>
> PLAN  SELECT
> COUNT(*)
> FROM (
> SELECT
> __C0_0 AS CUSTOMER_ID
> FROM PUBLIC.__T0
> GROUP BY __C0_0
> HAVING (SUM(__C0_1) > 2)
> OR (SUM(__C0_2) > 1)
> ) _18__Z3
> /* SELECT
> __C0_0 AS CUSTOMER_ID
> FROM PUBLIC.__T0
> /++ PUBLIC."merge_scan" ++/
> GROUP BY __C0_0
> HAVING (SUM(__C0_1) > 2)
> OR (SUM(__C0_2) > 1)
>  */
>
>
>
> However, I'm not sure it is "optimal" or not since I have no idea if it
> will perform better or worse on real data. That's why I need a subset of
> data which will make query execution speed readily visible. Unfortunately,
> I can't deduce that from query plan alone.
>
>
>
> Regards,
>
> --
>
> Ilya Kasnacheev
>
>
>
>
>
> пн, 24 сент. 2018 г. в 16:14, eugene miretsky :
>
> An easy way to reproduce would be to
>
>
>
> 1. Create table
>
> CREATE TABLE GA_DATA (
>
> customer_id bigint,
>
> dt timestamp,
>
> category_id int,
>
> product_views_app int,
>
> product_clict_app int,
>
> product_clict_web int,
>
> product_clict_web int,
>
> PRI

Re: Query 3x slower with index

2018-10-11 Thread eugene miretsky
Thanks!

Could you please clarfiy "*In case of a composite index, it will apply the
columns one by one"? *

Igntie (or rather H2?) needs to load the data into heap in order to do the
groupBy & aggregations. We were hoping that only data that matches the
category filter will be loaded.
*What does one by one mean when: (assuming and index *(customer_id,
category_id)*) *

   1. *The fiilter is on both customer  and category. What data will be
   loaded into Heap?*
   2. *The fitler is only on **category, and the customer is just used for
   groupBy. Will Ignite*
  1. * load one customer with all the rows, and apply the category
  filter in heap*
  2.  *load one customer, but load only the rows that pass the category
  fitler in heap*
  3. *load all the events that pass the category filter, and then group
  them by customer. *

*From out benchmarking so far it seems like 1 is happening. *

On Thu, Oct 11, 2018 at 1:28 PM Stanislav Lukyanov 
wrote:

> Hi,
>
>
>
> It is a rather lengthy thread and I can’t dive into details right now,
>
> but AFAICS the issue now is making affinity key index to work with a
> secondary index.
>
> The important things to understand is
>
>1. Ignite will only use one index per table
>2. In case of a composite index, it will apply the columns one by one
>3. The affinity key index should always go first as the first step is
>splitting the query by affinity key values
>
>
>
> So, to use index over the affinity key (customer_id) and a secondary index
> (category_id) one needs to create an index
>
> like (customer_id, category_id), in that order, with no columns in between.
>
> Note that index (customer_id, dt, category_id) can’t be used instead of it.
>
> On the other hand, (customer_id, category_id, dt) can - the last part of
> the index will be left unused.
>
>
>
> Thanks,
>
> Stan
>
>
>
> *From: *eugene miretsky 
> *Sent: *9 октября 2018 г. 19:40
> *To: *user@ignite.apache.org
> *Subject: *Re: Query 3x slower with index
>
>
>
> Hi Ilya,
>
>
>
> I have tried it, and got the same performance as forcing using category
> index in my initial benchmark - query is 3x slowers and uses only one
> thread.
>
>
>
> From my experiments so far it seems like Ignite can either (a) use
> affinity key and run queries in parallel, (b) use index but run the query
> on only one thread.
>
>
>
> Has anybody been able to run OLAP like queries in while using an index?
>
>
>
> Cheers,
>
> Eugene
>
>
>
> On Mon, Sep 24, 2018 at 10:55 AM Ilya Kasnacheev <
> ilya.kasnach...@gmail.com> wrote:
>
> Hello!
>
>
>
> I guess that using AFFINITY_KEY as index have something to do with the
> fact that GROUP BY really wants to work per-partition.
>
>
>
> I have the following query for you:
>
>
>
> 1: jdbc:ignite:thin://localhost> explain Select count(*) FROM( Select
> customer_id from (Select customer_id, product_views_app, product_clict_app
> from GA_DATA ga join table(category_id int = ( 117930, 175930,
> 175940,175945,101450)) cats on cats.category_id = ga.category_id) data
> group by customer_id having SUM(product_views_app) > 2 OR
> SUM(product_clict_app) > 1);
> PLAN  SELECT
> DATA__Z2.CUSTOMER_ID AS __C0_0,
> SUM(DATA__Z2.PRODUCT_VIEWS_APP) AS __C0_1,
> SUM(DATA__Z2.PRODUCT_CLICT_APP) AS __C0_2
> FROM (
> SELECT
> GA__Z0.CUSTOMER_ID,
> GA__Z0.PRODUCT_VIEWS_APP,
> GA__Z0.PRODUCT_CLICT_APP
> FROM TABLE(CATEGORY_ID INTEGER=(117930, 175930, 175940, 175945,
> 101450)) CATS__Z1
> INNER JOIN PUBLIC.GA_DATA GA__Z0
> ON 1=1
> WHERE CATS__Z1.CATEGORY_ID = GA__Z0.CATEGORY_ID
> ) DATA__Z2
> /* SELECT
> GA__Z0.CUSTOMER_ID,
> GA__Z0.PRODUCT_VIEWS_APP,
> GA__Z0.PRODUCT_CLICT_APP
> FROM TABLE(CATEGORY_ID INTEGER=(117930, 175930, 175940, 175945,
> 101450)) CATS__Z1
> /++ function ++/
> INNER JOIN PUBLIC.GA_DATA GA__Z0
> /++ PUBLIC.GA_CATEGORY_ID: CATEGORY_ID = CATS__Z1.CATEGORY_ID ++/
> ON 1=1
> WHERE CATS__Z1.CATEGORY_ID = GA__Z0.CATEGORY_ID
>  */
> GROUP BY DATA__Z2.CUSTOMER_ID
>
> PLAN  SELECT
> COUNT(*)
> FROM (
> SELECT
> __C0_0 AS CUSTOMER_ID
> FROM PUBLIC.__T0
> GROUP BY __C0_0
> HAVING (SUM(__C0_1) > 2)
> OR (SUM(__C0_2) > 1)
> ) _18__Z3
> /* SELECT
> __C0_0 AS CUSTOMER_ID
> FROM PUBLIC.__T0
> /++ PUBLIC."merge_scan" ++/
> GROUP BY __C0_0
> HAVING (SUM(__C0_1) > 2)
> OR (SUM(__C0_2) > 1)
>  */
>
>
>
> However

RE: Query 3x slower with index

2018-10-11 Thread Stanislav Lukyanov
Hi,

It is a rather lengthy thread and I can’t dive into details right now, 
but AFAICS the issue now is making affinity key index to work with a secondary 
index.
The important things to understand is
1) Ignite will only use one index per table
2) In case of a composite index, it will apply the columns one by one
3) The affinity key index should always go first as the first step is splitting 
the query by affinity key values

So, to use index over the affinity key (customer_id) and a secondary index 
(category_id) one needs to create an index 
like (customer_id, category_id), in that order, with no columns in between.
Note that index (customer_id, dt, category_id) can’t be used instead of it.
On the other hand, (customer_id, category_id, dt) can - the last part of the 
index will be left unused.

Thanks,
Stan

From: eugene miretsky
Sent: 9 октября 2018 г. 19:40
To: user@ignite.apache.org
Subject: Re: Query 3x slower with index

Hi Ilya, 

I have tried it, and got the same performance as forcing using category index 
in my initial benchmark - query is 3x slowers and uses only one thread. 

From my experiments so far it seems like Ignite can either (a) use affinity key 
and run queries in parallel, (b) use index but run the query on only one 
thread. 

Has anybody been able to run OLAP like queries in while using an index? 

Cheers,
Eugene

On Mon, Sep 24, 2018 at 10:55 AM Ilya Kasnacheev  
wrote:
Hello!

I guess that using AFFINITY_KEY as index have something to do with the fact 
that GROUP BY really wants to work per-partition.

I have the following query for you:

1: jdbc:ignite:thin://localhost> explain Select count(*) FROM( Select 
customer_id from (Select customer_id, product_views_app, product_clict_app from 
GA_DATA ga join table(category_id int = ( 117930, 175930, 
175940,175945,101450)) cats on cats.category_id = ga.category_id) data group by 
customer_id having SUM(product_views_app) > 2 OR  SUM(product_clict_app) > 1);
PLAN  SELECT
    DATA__Z2.CUSTOMER_ID AS __C0_0,
    SUM(DATA__Z2.PRODUCT_VIEWS_APP) AS __C0_1,
    SUM(DATA__Z2.PRODUCT_CLICT_APP) AS __C0_2
FROM (
    SELECT
    GA__Z0.CUSTOMER_ID,
    GA__Z0.PRODUCT_VIEWS_APP,
    GA__Z0.PRODUCT_CLICT_APP
    FROM TABLE(CATEGORY_ID INTEGER=(117930, 175930, 175940, 175945, 101450)) 
CATS__Z1
    INNER JOIN PUBLIC.GA_DATA GA__Z0
    ON 1=1
    WHERE CATS__Z1.CATEGORY_ID = GA__Z0.CATEGORY_ID
) DATA__Z2
    /* SELECT
    GA__Z0.CUSTOMER_ID,
    GA__Z0.PRODUCT_VIEWS_APP,
    GA__Z0.PRODUCT_CLICT_APP
    FROM TABLE(CATEGORY_ID INTEGER=(117930, 175930, 175940, 175945, 101450)) 
CATS__Z1
    /++ function ++/
    INNER JOIN PUBLIC.GA_DATA GA__Z0
    /++ PUBLIC.GA_CATEGORY_ID: CATEGORY_ID = CATS__Z1.CATEGORY_ID ++/
    ON 1=1
    WHERE CATS__Z1.CATEGORY_ID = GA__Z0.CATEGORY_ID
 */
GROUP BY DATA__Z2.CUSTOMER_ID

PLAN  SELECT
    COUNT(*)
FROM (
    SELECT
    __C0_0 AS CUSTOMER_ID
    FROM PUBLIC.__T0
    GROUP BY __C0_0
    HAVING (SUM(__C0_1) > 2)
    OR (SUM(__C0_2) > 1)
) _18__Z3
    /* SELECT
    __C0_0 AS CUSTOMER_ID
    FROM PUBLIC.__T0
    /++ PUBLIC."merge_scan" ++/
    GROUP BY __C0_0
    HAVING (SUM(__C0_1) > 2)
    OR (SUM(__C0_2) > 1)
 */

However, I'm not sure it is "optimal" or not since I have no idea if it will 
perform better or worse on real data. That's why I need a subset of data which 
will make query execution speed readily visible. Unfortunately, I can't deduce 
that from query plan alone.

Regards,
-- 
Ilya Kasnacheev


пн, 24 сент. 2018 г. в 16:14, eugene miretsky :
An easy way to reproduce would be to 

1. Create table
CREATE TABLE GA_DATA (
    customer_id bigint,
    dt timestamp,
    category_id int,
    product_views_app int,
    product_clict_app int,
    product_clict_web int,
    product_clict_web int,
    PRIMARY KEY (customer_id, dt, category_id)
) WITH "template=ga_template, backups=0, affinityKey=customer_id";

2. Create indexes
• CREATE INDEX ga_customer_id ON GA_Data (customer_id)
• CREATE INDEX ga_pKey ON GA_Data (customer_id, dt, category_id)
• CREATE INDEX ga_category_and_customer_id ON GA_Data (category_id, customer_id)
• CREATE INDEX ga_category_id ON GA_Data (category_id)
3. Run Explain on the following queries while trying forcing using different 
indexes
• Select count(*) FROM( 
Select customer_id from GA_DATA  use index (ga_category_id)
where category_id in (117930, 175930, 175940,175945,101450) 
group by customer_id having SUM(product_views_app) > 2 OR  
SUM(product_clicks_app) > 1 )

• Select count(*) FROM( 
    Select customer_id from GA_DATA ga use index (ga_pKey)
    join table(category_id int = ( 117930, 175930, 175940,175945,101450)) cats 
on cats.category_id = ga.category_id   
    group by customer_id having SUM(product_views_app) > 2 OR  
SUM(product_clicks_app) > 1 
) 

The execution plans will be similar to what I have posted earler. In 
particular, only on of (a) 

Re: Query 3x slower with index

2018-10-09 Thread eugene miretsky
Hi Ilya,

I have tried it, and got the same performance as forcing using category
index in my initial benchmark - query is 3x slowers and uses only one
thread.

>From my experiments so far it seems like Ignite can either (a) use
affinity key and run queries in parallel, (b) use index but run the query
on only one thread.

Has anybody been able to run OLAP like queries in while using an index?

Cheers,
Eugene

On Mon, Sep 24, 2018 at 10:55 AM Ilya Kasnacheev 
wrote:

> Hello!
>
> I guess that using AFFINITY_KEY as index have something to do with the
> fact that GROUP BY really wants to work per-partition.
>
> I have the following query for you:
>
> 1: jdbc:ignite:thin://localhost> explain Select count(*) FROM( Select
> customer_id from (Select customer_id, product_views_app, product_clict_app
> from GA_DATA ga join table(category_id int = ( 117930, 175930,
> 175940,175945,101450)) cats on cats.category_id = ga.category_id) data
> group by customer_id having SUM(product_views_app) > 2 OR
> SUM(product_clict_app) > 1);
> PLAN  SELECT
> DATA__Z2.CUSTOMER_ID AS __C0_0,
> SUM(DATA__Z2.PRODUCT_VIEWS_APP) AS __C0_1,
> SUM(DATA__Z2.PRODUCT_CLICT_APP) AS __C0_2
> FROM (
> SELECT
> GA__Z0.CUSTOMER_ID,
> GA__Z0.PRODUCT_VIEWS_APP,
> GA__Z0.PRODUCT_CLICT_APP
> FROM TABLE(CATEGORY_ID INTEGER=(117930, 175930, 175940, 175945,
> 101450)) CATS__Z1
> INNER JOIN PUBLIC.GA_DATA GA__Z0
> ON 1=1
> WHERE CATS__Z1.CATEGORY_ID = GA__Z0.CATEGORY_ID
> ) DATA__Z2
> /* SELECT
> GA__Z0.CUSTOMER_ID,
> GA__Z0.PRODUCT_VIEWS_APP,
> GA__Z0.PRODUCT_CLICT_APP
> FROM TABLE(CATEGORY_ID INTEGER=(117930, 175930, 175940, 175945,
> 101450)) CATS__Z1
> /++ function ++/
> INNER JOIN PUBLIC.GA_DATA GA__Z0
> /++ PUBLIC.GA_CATEGORY_ID: CATEGORY_ID = CATS__Z1.CATEGORY_ID ++/
> ON 1=1
> WHERE CATS__Z1.CATEGORY_ID = GA__Z0.CATEGORY_ID
>  */
> GROUP BY DATA__Z2.CUSTOMER_ID
>
> PLAN  SELECT
> COUNT(*)
> FROM (
> SELECT
> __C0_0 AS CUSTOMER_ID
> FROM PUBLIC.__T0
> GROUP BY __C0_0
> HAVING (SUM(__C0_1) > 2)
> OR (SUM(__C0_2) > 1)
> ) _18__Z3
> /* SELECT
> __C0_0 AS CUSTOMER_ID
> FROM PUBLIC.__T0
> /++ PUBLIC."merge_scan" ++/
> GROUP BY __C0_0
> HAVING (SUM(__C0_1) > 2)
> OR (SUM(__C0_2) > 1)
>  */
>
> However, I'm not sure it is "optimal" or not since I have no idea if it
> will perform better or worse on real data. That's why I need a subset of
> data which will make query execution speed readily visible. Unfortunately,
> I can't deduce that from query plan alone.
>
> Regards,
> --
> Ilya Kasnacheev
>
>
> пн, 24 сент. 2018 г. в 16:14, eugene miretsky :
>
>> An easy way to reproduce would be to
>>
>> 1. Create table
>>
>> CREATE TABLE GA_DATA (
>> customer_id bigint,
>> dt timestamp,
>> category_id int,
>> product_views_app int,
>> product_clict_app int,
>> product_clict_web int,
>> product_clict_web int,
>> PRIMARY KEY (customer_id, dt, category_id)
>> ) WITH "template=ga_template, backups=0, affinityKey=customer_id";
>>
>> 2. Create indexes
>>
>>- CREATE INDEX ga_customer_id ON GA_Data (customer_id)
>>- CREATE INDEX ga_pKey ON GA_Data (customer_id, dt, category_id)
>>- CREATE INDEX ga_category_and_customer_id ON GA_Data (category_id,
>>customer_id)
>>- CREATE INDEX ga_category_id ON GA_Data (category_id)
>>
>> 3. Run Explain on the following queries while trying forcing using
>> different indexes
>>
>>- Select count(*) FROM(
>>
>> Select customer_id from GA_DATA  use index (ga_category_id)
>> where category_id in (117930, 175930, 175940,175945,101450)
>> group by customer_id having SUM(product_views_app) > 2 OR
>> SUM(product_clicks_app) > 1 )
>>
>>
>>- Select count(*) FROM(
>>
>> Select customer_id from GA_DATA ga use index (ga_pKey)
>> join table(category_id int = ( 117930, 175930, 175940,175945,101450))
>> cats on cats.category_id = ga.category_id
>> group by customer_id having SUM(product_views_app) > 2 OR
>> SUM(product_clicks_app) > 1
>> )
>>
>> The execution plans will be similar to what I have posted earler. In
>> particular, only on of (a) affinty key index, (b) category_id index will be
>> used.
>>
>> On Fri, Sep 21, 2018 at 8:49 AM Ilya Kasnacheev <
>> ilya.kasnach...@gmail.com> wrote:
>>
>>> Hello!
>>>
>>> Can you share a reproducer project which loads (or generates) data for
>>> caches and then queries them? I could try and debug it if I had the
>>> reproducer.
>>>
>>> Regards.
>>> --
>>> Ilya Kasnacheev
>>>
>>>
>>> чт, 20 сент. 2018 г. в 21:05, eugene miretsky >> >:
>>>
 Thanks Ilya,

 Tried it, no luck. It performs the same as when using category_id index
 alone (slow).
   Any combindation I try either uses AFFINITY_KEY or category index.
 When it uses category index it runs slowers.

 Also, when AFFINITY_KEY key is used, the jobs runs on 

Re: Query 3x slower with index

2018-09-24 Thread Ilya Kasnacheev
Hello!

I guess that using AFFINITY_KEY as index have something to do with the fact
that GROUP BY really wants to work per-partition.

I have the following query for you:

1: jdbc:ignite:thin://localhost> explain Select count(*) FROM( Select
customer_id from (Select customer_id, product_views_app, product_clict_app
from GA_DATA ga join table(category_id int = ( 117930, 175930,
175940,175945,101450)) cats on cats.category_id = ga.category_id) data
group by customer_id having SUM(product_views_app) > 2 OR
SUM(product_clict_app) > 1);
PLAN  SELECT
DATA__Z2.CUSTOMER_ID AS __C0_0,
SUM(DATA__Z2.PRODUCT_VIEWS_APP) AS __C0_1,
SUM(DATA__Z2.PRODUCT_CLICT_APP) AS __C0_2
FROM (
SELECT
GA__Z0.CUSTOMER_ID,
GA__Z0.PRODUCT_VIEWS_APP,
GA__Z0.PRODUCT_CLICT_APP
FROM TABLE(CATEGORY_ID INTEGER=(117930, 175930, 175940, 175945,
101450)) CATS__Z1
INNER JOIN PUBLIC.GA_DATA GA__Z0
ON 1=1
WHERE CATS__Z1.CATEGORY_ID = GA__Z0.CATEGORY_ID
) DATA__Z2
/* SELECT
GA__Z0.CUSTOMER_ID,
GA__Z0.PRODUCT_VIEWS_APP,
GA__Z0.PRODUCT_CLICT_APP
FROM TABLE(CATEGORY_ID INTEGER=(117930, 175930, 175940, 175945,
101450)) CATS__Z1
/++ function ++/
INNER JOIN PUBLIC.GA_DATA GA__Z0
/++ PUBLIC.GA_CATEGORY_ID: CATEGORY_ID = CATS__Z1.CATEGORY_ID ++/
ON 1=1
WHERE CATS__Z1.CATEGORY_ID = GA__Z0.CATEGORY_ID
 */
GROUP BY DATA__Z2.CUSTOMER_ID

PLAN  SELECT
COUNT(*)
FROM (
SELECT
__C0_0 AS CUSTOMER_ID
FROM PUBLIC.__T0
GROUP BY __C0_0
HAVING (SUM(__C0_1) > 2)
OR (SUM(__C0_2) > 1)
) _18__Z3
/* SELECT
__C0_0 AS CUSTOMER_ID
FROM PUBLIC.__T0
/++ PUBLIC."merge_scan" ++/
GROUP BY __C0_0
HAVING (SUM(__C0_1) > 2)
OR (SUM(__C0_2) > 1)
 */

However, I'm not sure it is "optimal" or not since I have no idea if it
will perform better or worse on real data. That's why I need a subset of
data which will make query execution speed readily visible. Unfortunately,
I can't deduce that from query plan alone.

Regards,
-- 
Ilya Kasnacheev


пн, 24 сент. 2018 г. в 16:14, eugene miretsky :

> An easy way to reproduce would be to
>
> 1. Create table
>
> CREATE TABLE GA_DATA (
> customer_id bigint,
> dt timestamp,
> category_id int,
> product_views_app int,
> product_clict_app int,
> product_clict_web int,
> product_clict_web int,
> PRIMARY KEY (customer_id, dt, category_id)
> ) WITH "template=ga_template, backups=0, affinityKey=customer_id";
>
> 2. Create indexes
>
>- CREATE INDEX ga_customer_id ON GA_Data (customer_id)
>- CREATE INDEX ga_pKey ON GA_Data (customer_id, dt, category_id)
>- CREATE INDEX ga_category_and_customer_id ON GA_Data (category_id,
>customer_id)
>- CREATE INDEX ga_category_id ON GA_Data (category_id)
>
> 3. Run Explain on the following queries while trying forcing using
> different indexes
>
>- Select count(*) FROM(
>
> Select customer_id from GA_DATA  use index (ga_category_id)
> where category_id in (117930, 175930, 175940,175945,101450)
> group by customer_id having SUM(product_views_app) > 2 OR
> SUM(product_clicks_app) > 1 )
>
>
>- Select count(*) FROM(
>
> Select customer_id from GA_DATA ga use index (ga_pKey)
> join table(category_id int = ( 117930, 175930, 175940,175945,101450))
> cats on cats.category_id = ga.category_id
> group by customer_id having SUM(product_views_app) > 2 OR
> SUM(product_clicks_app) > 1
> )
>
> The execution plans will be similar to what I have posted earler. In
> particular, only on of (a) affinty key index, (b) category_id index will be
> used.
>
> On Fri, Sep 21, 2018 at 8:49 AM Ilya Kasnacheev 
> wrote:
>
>> Hello!
>>
>> Can you share a reproducer project which loads (or generates) data for
>> caches and then queries them? I could try and debug it if I had the
>> reproducer.
>>
>> Regards.
>> --
>> Ilya Kasnacheev
>>
>>
>> чт, 20 сент. 2018 г. в 21:05, eugene miretsky > >:
>>
>>> Thanks Ilya,
>>>
>>> Tried it, no luck. It performs the same as when using category_id index
>>> alone (slow).
>>>   Any combindation I try either uses AFFINITY_KEY or category index.
>>> When it uses category index it runs slowers.
>>>
>>> Also, when AFFINITY_KEY key is used, the jobs runs on 32 threads (my
>>> query parallelism settings ) when category_id is used, the jobs runs on one
>>> thread most of the time (first few seconds it looks like more threads are
>>> doing work).
>>>
>>> Please help on this. It seems like a very simple use case (using
>>> affinity key and another index), either I am doing something extremly
>>> silly, or I stumbled on a bug in Ignite that's effecting a lot of people.
>>>
>>> Cheers,
>>> Eugene
>>>
>>> On Thu, Sep 20, 2018 at 6:22 AM Ilya Kasnacheev <
>>> ilya.kasnach...@gmail.com> wrote:
>>>
 Hello!

 > 2) ga_customer_and_category_id: on customer_id and category_id

 Have you tried to do an index on category_id first, customer_id 

Re: Query 3x slower with index

2018-09-24 Thread eugene miretsky
An easy way to reproduce would be to

1. Create table

CREATE TABLE GA_DATA (
customer_id bigint,
dt timestamp,
category_id int,
product_views_app int,
product_clict_app int,
product_clict_web int,
product_clict_web int,
PRIMARY KEY (customer_id, dt, category_id)
) WITH "template=ga_template, backups=0, affinityKey=customer_id";

2. Create indexes

   - CREATE INDEX ga_customer_id ON GA_Data (customer_id)
   - CREATE INDEX ga_pKey ON GA_Data (customer_id, dt, category_id)
   - CREATE INDEX ga_category_and_customer_id ON GA_Data (category_id,
   customer_id)
   - CREATE INDEX ga_category_id ON GA_Data (category_id)

3. Run Explain on the following queries while trying forcing using
different indexes

   - Select count(*) FROM(

Select customer_id from GA_DATA  use index (ga_category_id)
where category_id in (117930, 175930, 175940,175945,101450)
group by customer_id having SUM(product_views_app) > 2 OR
SUM(product_clicks_app) > 1 )


   - Select count(*) FROM(

Select customer_id from GA_DATA ga use index (ga_pKey)
join table(category_id int = ( 117930, 175930, 175940,175945,101450))
cats on cats.category_id = ga.category_id
group by customer_id having SUM(product_views_app) > 2 OR
SUM(product_clicks_app) > 1
)

The execution plans will be similar to what I have posted earler. In
particular, only on of (a) affinty key index, (b) category_id index will be
used.

On Fri, Sep 21, 2018 at 8:49 AM Ilya Kasnacheev 
wrote:

> Hello!
>
> Can you share a reproducer project which loads (or generates) data for
> caches and then queries them? I could try and debug it if I had the
> reproducer.
>
> Regards.
> --
> Ilya Kasnacheev
>
>
> чт, 20 сент. 2018 г. в 21:05, eugene miretsky :
>
>> Thanks Ilya,
>>
>> Tried it, no luck. It performs the same as when using category_id index
>> alone (slow).
>>   Any combindation I try either uses AFFINITY_KEY or category index. When
>> it uses category index it runs slowers.
>>
>> Also, when AFFINITY_KEY key is used, the jobs runs on 32 threads (my
>> query parallelism settings ) when category_id is used, the jobs runs on one
>> thread most of the time (first few seconds it looks like more threads are
>> doing work).
>>
>> Please help on this. It seems like a very simple use case (using affinity
>> key and another index), either I am doing something extremly silly, or I
>> stumbled on a bug in Ignite that's effecting a lot of people.
>>
>> Cheers,
>> Eugene
>>
>> On Thu, Sep 20, 2018 at 6:22 AM Ilya Kasnacheev <
>> ilya.kasnach...@gmail.com> wrote:
>>
>>> Hello!
>>>
>>> > 2) ga_customer_and_category_id: on customer_id and category_id
>>>
>>> Have you tried to do an index on category_id first, customer_id second?
>>> Note that Ignite will use only one index when joining two tables and that
>>> in your case it should start with category_id.
>>>
>>> You can also try adding affinity key to this index in various places,
>>> see if it helps further.
>>>
>>> Regards,
>>> --
>>> Ilya Kasnacheev
>>>
>>>
>>> ср, 19 сент. 2018 г. в 21:27, eugene miretsky >> >:
>>>
 Hi Ilya,

 I created 4 indexs on the table:
 1) ga_pKey: on customer_id, dt, category_id (that's our primary key
 columns)
 2) ga_customer_and_category_id: on customer_id and category_id
 2) ga_customer_id: on customer_id
 4) ga_category_id: on category_id


 For the first query (category in ()), the execution plan when using the
 first 3 index is exactly the same  - using /* PUBLIC.AFFINITY_KEY */
 When using #4 (alone or in combination with any of the other 3)

1. /* PUBLIC.AFFINITY_KEY */ is replaced with  /*
PUBLIC.GA_CATEGORY_ID: CATEGORY_ID IN(117930, 175930, 175940, 175945,
101450) */
2. The query runs slower.

 For the second query (join on an inlined table) the behaviour is very
 similar. Using the first 3 indexes results in the same plan - using  /*
 PUBLIC.AFFINITY_KEY */ and  /* function: CATEGORY_ID = GA__Z0.CATEGORY_ID
 */.
 When using #4 (alone or in combination with any of the other 3)

1. /* function */ and /* PUBLIC.GA_CATEGORY_ID: CATEGORY_ID =
CATS__Z1.CATEGORY_ID */ are used
2. The query is much slower.


 Theoretically the query seems pretty simple

1. Use affinity key  to make sure the query runs in parallel and
there are no shuffles
2. Filter rows that match category_id using the category_id index
3. Used customer_id index for the group_by (not sure if this step
makes sense)

 But I cannot get it to work.

 Cheers,
 Eugene




 On Tue, Sep 18, 2018 at 10:56 AM Ilya Kasnacheev <
 ilya.kasnach...@gmail.com> wrote:

> Hello!
>
> I can see you try to use _key_PK as index. If your primary key is
> composite, it won't work properly for you. I recommend creating an 
> explicit
> (category_id, customer_id) 

Re: Query 3x slower with index

2018-09-21 Thread Ilya Kasnacheev
Hello!

Can you share a reproducer project which loads (or generates) data for
caches and then queries them? I could try and debug it if I had the
reproducer.

Regards.
-- 
Ilya Kasnacheev


чт, 20 сент. 2018 г. в 21:05, eugene miretsky :

> Thanks Ilya,
>
> Tried it, no luck. It performs the same as when using category_id index
> alone (slow).
>   Any combindation I try either uses AFFINITY_KEY or category index. When
> it uses category index it runs slowers.
>
> Also, when AFFINITY_KEY key is used, the jobs runs on 32 threads (my query
> parallelism settings ) when category_id is used, the jobs runs on one
> thread most of the time (first few seconds it looks like more threads are
> doing work).
>
> Please help on this. It seems like a very simple use case (using affinity
> key and another index), either I am doing something extremly silly, or I
> stumbled on a bug in Ignite that's effecting a lot of people.
>
> Cheers,
> Eugene
>
> On Thu, Sep 20, 2018 at 6:22 AM Ilya Kasnacheev 
> wrote:
>
>> Hello!
>>
>> > 2) ga_customer_and_category_id: on customer_id and category_id
>>
>> Have you tried to do an index on category_id first, customer_id second?
>> Note that Ignite will use only one index when joining two tables and that
>> in your case it should start with category_id.
>>
>> You can also try adding affinity key to this index in various places, see
>> if it helps further.
>>
>> Regards,
>> --
>> Ilya Kasnacheev
>>
>>
>> ср, 19 сент. 2018 г. в 21:27, eugene miretsky > >:
>>
>>> Hi Ilya,
>>>
>>> I created 4 indexs on the table:
>>> 1) ga_pKey: on customer_id, dt, category_id (that's our primary key
>>> columns)
>>> 2) ga_customer_and_category_id: on customer_id and category_id
>>> 2) ga_customer_id: on customer_id
>>> 4) ga_category_id: on category_id
>>>
>>>
>>> For the first query (category in ()), the execution plan when using the
>>> first 3 index is exactly the same  - using /* PUBLIC.AFFINITY_KEY */
>>> When using #4 (alone or in combination with any of the other 3)
>>>
>>>1. /* PUBLIC.AFFINITY_KEY */ is replaced with  /*
>>>PUBLIC.GA_CATEGORY_ID: CATEGORY_ID IN(117930, 175930, 175940, 175945,
>>>101450) */
>>>2. The query runs slower.
>>>
>>> For the second query (join on an inlined table) the behaviour is very
>>> similar. Using the first 3 indexes results in the same plan - using  /*
>>> PUBLIC.AFFINITY_KEY */ and  /* function: CATEGORY_ID = GA__Z0.CATEGORY_ID
>>> */.
>>> When using #4 (alone or in combination with any of the other 3)
>>>
>>>1. /* function */ and /* PUBLIC.GA_CATEGORY_ID: CATEGORY_ID =
>>>CATS__Z1.CATEGORY_ID */ are used
>>>2. The query is much slower.
>>>
>>>
>>> Theoretically the query seems pretty simple
>>>
>>>1. Use affinity key  to make sure the query runs in parallel and
>>>there are no shuffles
>>>2. Filter rows that match category_id using the category_id index
>>>3. Used customer_id index for the group_by (not sure if this step
>>>makes sense)
>>>
>>> But I cannot get it to work.
>>>
>>> Cheers,
>>> Eugene
>>>
>>>
>>>
>>>
>>> On Tue, Sep 18, 2018 at 10:56 AM Ilya Kasnacheev <
>>> ilya.kasnach...@gmail.com> wrote:
>>>
 Hello!

 I can see you try to use _key_PK as index. If your primary key is
 composite, it won't work properly for you. I recommend creating an explicit
 (category_id, customer_id) index.

 Regards,
 --
 Ilya Kasnacheev


 вт, 18 сент. 2018 г. в 17:47, eugene miretsky <
 eugene.miret...@gmail.com>:

> Hi Ilya,
>
> The different query result was my mistake - one of the categoy_ids was
> duplicate, so in the query that used join, it counted rows for that
> category twice. My apologies.
>
> However, we are still having an issue with query time, and the index
> not being applied to category_id. Would appreciate if you could take a
> look.
>
> Cheers,
> Eugene
>
> On Mon, Sep 17, 2018 at 9:15 AM Ilya Kasnacheev <
> ilya.kasnach...@gmail.com> wrote:
>
>> Hello!
>>
>> Why don't you diff the results of those two queries, tell us what the
>> difference is?
>>
>> Regards,
>> --
>> Ilya Kasnacheev
>>
>>
>> пн, 17 сент. 2018 г. в 16:08, eugene miretsky <
>> eugene.miret...@gmail.com>:
>>
>>> Hello,
>>>
>>> Just wanted to see if anybody had time to look into this.
>>>
>>> Cheers,
>>> Eugene
>>>
>>> On Wed, Sep 12, 2018 at 6:29 PM eugene miretsky <
>>> eugene.miret...@gmail.com> wrote:
>>>
 Thanks!

 Tried joining with an inlined table instead of IN as per the second
 suggestion, and it didn't quite work.

 Query1:

- Select COUNT(*) FROM( Select customer_id from GATABLE3  use
Index( ) where category_id in (9005, 175930, 175930, 
 175940,175945,101450,
6453) group by customer_id having SUM(product_views_app) > 2 OR

Re: Query 3x slower with index

2018-09-20 Thread eugene miretsky
Thanks Ilya,

Tried it, no luck. It performs the same as when using category_id index
alone (slow).
  Any combindation I try either uses AFFINITY_KEY or category index. When
it uses category index it runs slowers.

Also, when AFFINITY_KEY key is used, the jobs runs on 32 threads (my query
parallelism settings ) when category_id is used, the jobs runs on one
thread most of the time (first few seconds it looks like more threads are
doing work).

Please help on this. It seems like a very simple use case (using affinity
key and another index), either I am doing something extremly silly, or I
stumbled on a bug in Ignite that's effecting a lot of people.

Cheers,
Eugene

On Thu, Sep 20, 2018 at 6:22 AM Ilya Kasnacheev 
wrote:

> Hello!
>
> > 2) ga_customer_and_category_id: on customer_id and category_id
>
> Have you tried to do an index on category_id first, customer_id second?
> Note that Ignite will use only one index when joining two tables and that
> in your case it should start with category_id.
>
> You can also try adding affinity key to this index in various places, see
> if it helps further.
>
> Regards,
> --
> Ilya Kasnacheev
>
>
> ср, 19 сент. 2018 г. в 21:27, eugene miretsky :
>
>> Hi Ilya,
>>
>> I created 4 indexs on the table:
>> 1) ga_pKey: on customer_id, dt, category_id (that's our primary key
>> columns)
>> 2) ga_customer_and_category_id: on customer_id and category_id
>> 2) ga_customer_id: on customer_id
>> 4) ga_category_id: on category_id
>>
>>
>> For the first query (category in ()), the execution plan when using the
>> first 3 index is exactly the same  - using /* PUBLIC.AFFINITY_KEY */
>> When using #4 (alone or in combination with any of the other 3)
>>
>>1. /* PUBLIC.AFFINITY_KEY */ is replaced with  /*
>>PUBLIC.GA_CATEGORY_ID: CATEGORY_ID IN(117930, 175930, 175940, 175945,
>>101450) */
>>2. The query runs slower.
>>
>> For the second query (join on an inlined table) the behaviour is very
>> similar. Using the first 3 indexes results in the same plan - using  /*
>> PUBLIC.AFFINITY_KEY */ and  /* function: CATEGORY_ID = GA__Z0.CATEGORY_ID
>> */.
>> When using #4 (alone or in combination with any of the other 3)
>>
>>1. /* function */ and /* PUBLIC.GA_CATEGORY_ID: CATEGORY_ID =
>>CATS__Z1.CATEGORY_ID */ are used
>>2. The query is much slower.
>>
>>
>> Theoretically the query seems pretty simple
>>
>>1. Use affinity key  to make sure the query runs in parallel and
>>there are no shuffles
>>2. Filter rows that match category_id using the category_id index
>>3. Used customer_id index for the group_by (not sure if this step
>>makes sense)
>>
>> But I cannot get it to work.
>>
>> Cheers,
>> Eugene
>>
>>
>>
>>
>> On Tue, Sep 18, 2018 at 10:56 AM Ilya Kasnacheev <
>> ilya.kasnach...@gmail.com> wrote:
>>
>>> Hello!
>>>
>>> I can see you try to use _key_PK as index. If your primary key is
>>> composite, it won't work properly for you. I recommend creating an explicit
>>> (category_id, customer_id) index.
>>>
>>> Regards,
>>> --
>>> Ilya Kasnacheev
>>>
>>>
>>> вт, 18 сент. 2018 г. в 17:47, eugene miretsky >> >:
>>>
 Hi Ilya,

 The different query result was my mistake - one of the categoy_ids was
 duplicate, so in the query that used join, it counted rows for that
 category twice. My apologies.

 However, we are still having an issue with query time, and the index
 not being applied to category_id. Would appreciate if you could take a
 look.

 Cheers,
 Eugene

 On Mon, Sep 17, 2018 at 9:15 AM Ilya Kasnacheev <
 ilya.kasnach...@gmail.com> wrote:

> Hello!
>
> Why don't you diff the results of those two queries, tell us what the
> difference is?
>
> Regards,
> --
> Ilya Kasnacheev
>
>
> пн, 17 сент. 2018 г. в 16:08, eugene miretsky <
> eugene.miret...@gmail.com>:
>
>> Hello,
>>
>> Just wanted to see if anybody had time to look into this.
>>
>> Cheers,
>> Eugene
>>
>> On Wed, Sep 12, 2018 at 6:29 PM eugene miretsky <
>> eugene.miret...@gmail.com> wrote:
>>
>>> Thanks!
>>>
>>> Tried joining with an inlined table instead of IN as per the second
>>> suggestion, and it didn't quite work.
>>>
>>> Query1:
>>>
>>>- Select COUNT(*) FROM( Select customer_id from GATABLE3  use
>>>Index( ) where category_id in (9005, 175930, 175930, 
>>> 175940,175945,101450,
>>>6453) group by customer_id having SUM(product_views_app) > 2 OR
>>>SUM(product_clicks_app) > 1 )
>>>- exec time = 17s
>>>- *Result: 3105868*
>>>- Same exec time if using AFFINITY_KEY index or "_key_PK_hash or
>>>customer_id index
>>>- Using an index on category_id increases the query time 33s
>>>
>>> Query2:
>>>
>>>- Select COUNT(*) FROM( Select customer_id from GATABLE3 ga  use
>>>index (PUBLIC."_key_PK") inner join 

Re: Query 3x slower with index

2018-09-20 Thread Ilya Kasnacheev
Hello!

> 2) ga_customer_and_category_id: on customer_id and category_id

Have you tried to do an index on category_id first, customer_id second?
Note that Ignite will use only one index when joining two tables and that
in your case it should start with category_id.

You can also try adding affinity key to this index in various places, see
if it helps further.

Regards,
-- 
Ilya Kasnacheev


ср, 19 сент. 2018 г. в 21:27, eugene miretsky :

> Hi Ilya,
>
> I created 4 indexs on the table:
> 1) ga_pKey: on customer_id, dt, category_id (that's our primary key
> columns)
> 2) ga_customer_and_category_id: on customer_id and category_id
> 2) ga_customer_id: on customer_id
> 4) ga_category_id: on category_id
>
>
> For the first query (category in ()), the execution plan when using the
> first 3 index is exactly the same  - using /* PUBLIC.AFFINITY_KEY */
> When using #4 (alone or in combination with any of the other 3)
>
>1. /* PUBLIC.AFFINITY_KEY */ is replaced with  /*
>PUBLIC.GA_CATEGORY_ID: CATEGORY_ID IN(117930, 175930, 175940, 175945,
>101450) */
>2. The query runs slower.
>
> For the second query (join on an inlined table) the behaviour is very
> similar. Using the first 3 indexes results in the same plan - using  /*
> PUBLIC.AFFINITY_KEY */ and  /* function: CATEGORY_ID = GA__Z0.CATEGORY_ID
> */.
> When using #4 (alone or in combination with any of the other 3)
>
>1. /* function */ and /* PUBLIC.GA_CATEGORY_ID: CATEGORY_ID =
>CATS__Z1.CATEGORY_ID */ are used
>2. The query is much slower.
>
>
> Theoretically the query seems pretty simple
>
>1. Use affinity key  to make sure the query runs in parallel and there
>are no shuffles
>2. Filter rows that match category_id using the category_id index
>3. Used customer_id index for the group_by (not sure if this step
>makes sense)
>
> But I cannot get it to work.
>
> Cheers,
> Eugene
>
>
>
>
> On Tue, Sep 18, 2018 at 10:56 AM Ilya Kasnacheev <
> ilya.kasnach...@gmail.com> wrote:
>
>> Hello!
>>
>> I can see you try to use _key_PK as index. If your primary key is
>> composite, it won't work properly for you. I recommend creating an explicit
>> (category_id, customer_id) index.
>>
>> Regards,
>> --
>> Ilya Kasnacheev
>>
>>
>> вт, 18 сент. 2018 г. в 17:47, eugene miretsky > >:
>>
>>> Hi Ilya,
>>>
>>> The different query result was my mistake - one of the categoy_ids was
>>> duplicate, so in the query that used join, it counted rows for that
>>> category twice. My apologies.
>>>
>>> However, we are still having an issue with query time, and the index not
>>> being applied to category_id. Would appreciate if you could take a look.
>>>
>>> Cheers,
>>> Eugene
>>>
>>> On Mon, Sep 17, 2018 at 9:15 AM Ilya Kasnacheev <
>>> ilya.kasnach...@gmail.com> wrote:
>>>
 Hello!

 Why don't you diff the results of those two queries, tell us what the
 difference is?

 Regards,
 --
 Ilya Kasnacheev


 пн, 17 сент. 2018 г. в 16:08, eugene miretsky <
 eugene.miret...@gmail.com>:

> Hello,
>
> Just wanted to see if anybody had time to look into this.
>
> Cheers,
> Eugene
>
> On Wed, Sep 12, 2018 at 6:29 PM eugene miretsky <
> eugene.miret...@gmail.com> wrote:
>
>> Thanks!
>>
>> Tried joining with an inlined table instead of IN as per the second
>> suggestion, and it didn't quite work.
>>
>> Query1:
>>
>>- Select COUNT(*) FROM( Select customer_id from GATABLE3  use
>>Index( ) where category_id in (9005, 175930, 175930, 
>> 175940,175945,101450,
>>6453) group by customer_id having SUM(product_views_app) > 2 OR
>>SUM(product_clicks_app) > 1 )
>>- exec time = 17s
>>- *Result: 3105868*
>>- Same exec time if using AFFINITY_KEY index or "_key_PK_hash or
>>customer_id index
>>- Using an index on category_id increases the query time 33s
>>
>> Query2:
>>
>>- Select COUNT(*) FROM( Select customer_id from GATABLE3 ga  use
>>index (PUBLIC."_key_PK") inner join table(category_id int = (9005, 
>> 175930,
>>175930, 175940,175945,101450, 6453)) cats on cats.category_id =
>>ga.category_id   group by customer_id having SUM(product_views_app) > 
>> 2 OR
>>SUM(product_clicks_app) > 1 )
>>- exec time = 38s
>>- *Result: 3113921*
>>- Same exec time if using AFFINITY_KEY index or "_key_PK_hash or
>>customer_id index or category_id index
>>- Using an index on category_id doesnt change the run time
>>
>> Query plans are attached.
>>
>> 3 questions:
>>
>>1. Why is the result differnt for the 2 queries - this is quite
>>concerning.
>>2. Why is the 2nd query taking longer
>>3. Why  category_id index doesn't work in case of query 2.
>>
>>
>> On Wed, Sep 5, 2018 at 8:31 AM Ilya Kasnacheev <
>> 

Re: Query 3x slower with index

2018-09-19 Thread eugene miretsky
Hi Ilya,

I created 4 indexs on the table:
1) ga_pKey: on customer_id, dt, category_id (that's our primary key columns)
2) ga_customer_and_category_id: on customer_id and category_id
2) ga_customer_id: on customer_id
4) ga_category_id: on category_id


For the first query (category in ()), the execution plan when using the
first 3 index is exactly the same  - using /* PUBLIC.AFFINITY_KEY */
When using #4 (alone or in combination with any of the other 3)

   1. /* PUBLIC.AFFINITY_KEY */ is replaced with  /* PUBLIC.GA_CATEGORY_ID:
   CATEGORY_ID IN(117930, 175930, 175940, 175945, 101450) */
   2. The query runs slower.

For the second query (join on an inlined table) the behaviour is very
similar. Using the first 3 indexes results in the same plan - using  /*
PUBLIC.AFFINITY_KEY */ and  /* function: CATEGORY_ID = GA__Z0.CATEGORY_ID
*/.
When using #4 (alone or in combination with any of the other 3)

   1. /* function */ and /* PUBLIC.GA_CATEGORY_ID: CATEGORY_ID =
   CATS__Z1.CATEGORY_ID */ are used
   2. The query is much slower.


Theoretically the query seems pretty simple

   1. Use affinity key  to make sure the query runs in parallel and there
   are no shuffles
   2. Filter rows that match category_id using the category_id index
   3. Used customer_id index for the group_by (not sure if this step makes
   sense)

But I cannot get it to work.

Cheers,
Eugene




On Tue, Sep 18, 2018 at 10:56 AM Ilya Kasnacheev 
wrote:

> Hello!
>
> I can see you try to use _key_PK as index. If your primary key is
> composite, it won't work properly for you. I recommend creating an explicit
> (category_id, customer_id) index.
>
> Regards,
> --
> Ilya Kasnacheev
>
>
> вт, 18 сент. 2018 г. в 17:47, eugene miretsky :
>
>> Hi Ilya,
>>
>> The different query result was my mistake - one of the categoy_ids was
>> duplicate, so in the query that used join, it counted rows for that
>> category twice. My apologies.
>>
>> However, we are still having an issue with query time, and the index not
>> being applied to category_id. Would appreciate if you could take a look.
>>
>> Cheers,
>> Eugene
>>
>> On Mon, Sep 17, 2018 at 9:15 AM Ilya Kasnacheev <
>> ilya.kasnach...@gmail.com> wrote:
>>
>>> Hello!
>>>
>>> Why don't you diff the results of those two queries, tell us what the
>>> difference is?
>>>
>>> Regards,
>>> --
>>> Ilya Kasnacheev
>>>
>>>
>>> пн, 17 сент. 2018 г. в 16:08, eugene miretsky >> >:
>>>
 Hello,

 Just wanted to see if anybody had time to look into this.

 Cheers,
 Eugene

 On Wed, Sep 12, 2018 at 6:29 PM eugene miretsky <
 eugene.miret...@gmail.com> wrote:

> Thanks!
>
> Tried joining with an inlined table instead of IN as per the second
> suggestion, and it didn't quite work.
>
> Query1:
>
>- Select COUNT(*) FROM( Select customer_id from GATABLE3  use
>Index( ) where category_id in (9005, 175930, 175930, 
> 175940,175945,101450,
>6453) group by customer_id having SUM(product_views_app) > 2 OR
>SUM(product_clicks_app) > 1 )
>- exec time = 17s
>- *Result: 3105868*
>- Same exec time if using AFFINITY_KEY index or "_key_PK_hash or
>customer_id index
>- Using an index on category_id increases the query time 33s
>
> Query2:
>
>- Select COUNT(*) FROM( Select customer_id from GATABLE3 ga  use
>index (PUBLIC."_key_PK") inner join table(category_id int = (9005, 
> 175930,
>175930, 175940,175945,101450, 6453)) cats on cats.category_id =
>ga.category_id   group by customer_id having SUM(product_views_app) > 
> 2 OR
>SUM(product_clicks_app) > 1 )
>- exec time = 38s
>- *Result: 3113921*
>- Same exec time if using AFFINITY_KEY index or "_key_PK_hash or
>customer_id index or category_id index
>- Using an index on category_id doesnt change the run time
>
> Query plans are attached.
>
> 3 questions:
>
>1. Why is the result differnt for the 2 queries - this is quite
>concerning.
>2. Why is the 2nd query taking longer
>3. Why  category_id index doesn't work in case of query 2.
>
>
> On Wed, Sep 5, 2018 at 8:31 AM Ilya Kasnacheev <
> ilya.kasnach...@gmail.com> wrote:
>
>> Hello!
>>
>> I don't think that we're able to use index with IN () clauses. Please
>> convert it into OR clauses.
>>
>> Please see
>> https://apacheignite-sql.readme.io/docs/performance-and-debugging#section-sql-performance-and-usability-considerations
>>
>> Regards,
>> --
>> Ilya Kasnacheev
>>
>>
>> пн, 3 сент. 2018 г. в 12:46, Andrey Mashenkov <
>> andrey.mashen...@gmail.com>:
>>
>>> Hi
>>>
>>> Actually, first query uses index on affinity key which looks more
>>> efficient than index on category_id column.
>>> The first query can process groups one by one and stream partial

Re: Query 3x slower with index

2018-09-18 Thread Ilya Kasnacheev
Hello!

I can see you try to use _key_PK as index. If your primary key is
composite, it won't work properly for you. I recommend creating an explicit
(category_id, customer_id) index.

Regards,
-- 
Ilya Kasnacheev


вт, 18 сент. 2018 г. в 17:47, eugene miretsky :

> Hi Ilya,
>
> The different query result was my mistake - one of the categoy_ids was
> duplicate, so in the query that used join, it counted rows for that
> category twice. My apologies.
>
> However, we are still having an issue with query time, and the index not
> being applied to category_id. Would appreciate if you could take a look.
>
> Cheers,
> Eugene
>
> On Mon, Sep 17, 2018 at 9:15 AM Ilya Kasnacheev 
> wrote:
>
>> Hello!
>>
>> Why don't you diff the results of those two queries, tell us what the
>> difference is?
>>
>> Regards,
>> --
>> Ilya Kasnacheev
>>
>>
>> пн, 17 сент. 2018 г. в 16:08, eugene miretsky > >:
>>
>>> Hello,
>>>
>>> Just wanted to see if anybody had time to look into this.
>>>
>>> Cheers,
>>> Eugene
>>>
>>> On Wed, Sep 12, 2018 at 6:29 PM eugene miretsky <
>>> eugene.miret...@gmail.com> wrote:
>>>
 Thanks!

 Tried joining with an inlined table instead of IN as per the second
 suggestion, and it didn't quite work.

 Query1:

- Select COUNT(*) FROM( Select customer_id from GATABLE3  use
Index( ) where category_id in (9005, 175930, 175930, 
 175940,175945,101450,
6453) group by customer_id having SUM(product_views_app) > 2 OR
SUM(product_clicks_app) > 1 )
- exec time = 17s
- *Result: 3105868*
- Same exec time if using AFFINITY_KEY index or "_key_PK_hash or
customer_id index
- Using an index on category_id increases the query time 33s

 Query2:

- Select COUNT(*) FROM( Select customer_id from GATABLE3 ga  use
index (PUBLIC."_key_PK") inner join table(category_id int = (9005, 
 175930,
175930, 175940,175945,101450, 6453)) cats on cats.category_id =
ga.category_id   group by customer_id having SUM(product_views_app) > 2 
 OR
SUM(product_clicks_app) > 1 )
- exec time = 38s
- *Result: 3113921*
- Same exec time if using AFFINITY_KEY index or "_key_PK_hash or
customer_id index or category_id index
- Using an index on category_id doesnt change the run time

 Query plans are attached.

 3 questions:

1. Why is the result differnt for the 2 queries - this is quite
concerning.
2. Why is the 2nd query taking longer
3. Why  category_id index doesn't work in case of query 2.


 On Wed, Sep 5, 2018 at 8:31 AM Ilya Kasnacheev <
 ilya.kasnach...@gmail.com> wrote:

> Hello!
>
> I don't think that we're able to use index with IN () clauses. Please
> convert it into OR clauses.
>
> Please see
> https://apacheignite-sql.readme.io/docs/performance-and-debugging#section-sql-performance-and-usability-considerations
>
> Regards,
> --
> Ilya Kasnacheev
>
>
> пн, 3 сент. 2018 г. в 12:46, Andrey Mashenkov <
> andrey.mashen...@gmail.com>:
>
>> Hi
>>
>> Actually, first query uses index on affinity key which looks more
>> efficient than index on category_id column.
>> The first query can process groups one by one and stream partial
>> results from map phase to reduce phase as it use sorted index lookup,
>> while second query should process full dataset on map phase before
>> pass it for reducing.
>>
>> Try to use composite index (customer_id, category_id).
>>
>> Also, SqlQueryFields.setCollocated(true) flag can help Ignite to
>> build more efficient plan when group by on collocated column is used.
>>
>> On Sun, Sep 2, 2018 at 2:02 AM eugene miretsky <
>> eugene.miret...@gmail.com> wrote:
>>
>>> Hello,
>>>
>>> Schema:
>>>
>>>-
>>>
>>>PUBLIC.GATABLE2.CUSTOMER_ID
>>>
>>>PUBLIC.GATABLE2.DT
>>>
>>>PUBLIC.GATABLE2.CATEGORY_ID
>>>
>>>PUBLIC.GATABLE2.VERTICAL_ID
>>>
>>>PUBLIC.GATABLE2.SERVICE
>>>
>>>PUBLIC.GATABLE2.PRODUCT_VIEWS_APP
>>>
>>>PUBLIC.GATABLE2.PRODUCT_CLICKS_APP
>>>
>>>PUBLIC.GATABLE2.PRODUCT_VIEWS_WEB
>>>
>>>PUBLIC.GATABLE2.PRODUCT_CLICKS_WEB
>>>
>>>PUBLIC.GATABLE2.PDP_SESSIONS_APP
>>>
>>>PUBLIC.GATABLE2.PDP_SESSIONS_WEB
>>>- pkey = customer_id,dt
>>>- affinityKey = customer
>>>
>>> Query:
>>>
>>>- select COUNT(*) FROM( Select customer_id from GATABLE2 where
>>>category_id in (175925, 101450, 9005, 175930, 175930, 
>>> 175940,175945,101450,
>>>6453) group by customer_id having SUM(product_views_app) > 2 OR
>>>SUM(product_clicks_app) > 1 )
>>>
>>> The table has 600M rows.
>>> At first, the query took 1m, when we added an 

Re: Query 3x slower with index

2018-09-18 Thread eugene miretsky
Hi Ilya,

The different query result was my mistake - one of the categoy_ids was
duplicate, so in the query that used join, it counted rows for that
category twice. My apologies.

However, we are still having an issue with query time, and the index not
being applied to category_id. Would appreciate if you could take a look.

Cheers,
Eugene

On Mon, Sep 17, 2018 at 9:15 AM Ilya Kasnacheev 
wrote:

> Hello!
>
> Why don't you diff the results of those two queries, tell us what the
> difference is?
>
> Regards,
> --
> Ilya Kasnacheev
>
>
> пн, 17 сент. 2018 г. в 16:08, eugene miretsky :
>
>> Hello,
>>
>> Just wanted to see if anybody had time to look into this.
>>
>> Cheers,
>> Eugene
>>
>> On Wed, Sep 12, 2018 at 6:29 PM eugene miretsky <
>> eugene.miret...@gmail.com> wrote:
>>
>>> Thanks!
>>>
>>> Tried joining with an inlined table instead of IN as per the second
>>> suggestion, and it didn't quite work.
>>>
>>> Query1:
>>>
>>>- Select COUNT(*) FROM( Select customer_id from GATABLE3  use Index(
>>>) where category_id in (9005, 175930, 175930, 175940,175945,101450, 6453)
>>>group by customer_id having SUM(product_views_app) > 2 OR
>>>SUM(product_clicks_app) > 1 )
>>>- exec time = 17s
>>>- *Result: 3105868*
>>>- Same exec time if using AFFINITY_KEY index or "_key_PK_hash or
>>>customer_id index
>>>- Using an index on category_id increases the query time 33s
>>>
>>> Query2:
>>>
>>>- Select COUNT(*) FROM( Select customer_id from GATABLE3 ga  use
>>>index (PUBLIC."_key_PK") inner join table(category_id int = (9005, 
>>> 175930,
>>>175930, 175940,175945,101450, 6453)) cats on cats.category_id =
>>>ga.category_id   group by customer_id having SUM(product_views_app) > 2 
>>> OR
>>>SUM(product_clicks_app) > 1 )
>>>- exec time = 38s
>>>- *Result: 3113921*
>>>- Same exec time if using AFFINITY_KEY index or "_key_PK_hash or
>>>customer_id index or category_id index
>>>- Using an index on category_id doesnt change the run time
>>>
>>> Query plans are attached.
>>>
>>> 3 questions:
>>>
>>>1. Why is the result differnt for the 2 queries - this is quite
>>>concerning.
>>>2. Why is the 2nd query taking longer
>>>3. Why  category_id index doesn't work in case of query 2.
>>>
>>>
>>> On Wed, Sep 5, 2018 at 8:31 AM Ilya Kasnacheev <
>>> ilya.kasnach...@gmail.com> wrote:
>>>
 Hello!

 I don't think that we're able to use index with IN () clauses. Please
 convert it into OR clauses.

 Please see
 https://apacheignite-sql.readme.io/docs/performance-and-debugging#section-sql-performance-and-usability-considerations

 Regards,
 --
 Ilya Kasnacheev


 пн, 3 сент. 2018 г. в 12:46, Andrey Mashenkov <
 andrey.mashen...@gmail.com>:

> Hi
>
> Actually, first query uses index on affinity key which looks more
> efficient than index on category_id column.
> The first query can process groups one by one and stream partial
> results from map phase to reduce phase as it use sorted index lookup,
> while second query should process full dataset on map phase before
> pass it for reducing.
>
> Try to use composite index (customer_id, category_id).
>
> Also, SqlQueryFields.setCollocated(true) flag can help Ignite to build
> more efficient plan when group by on collocated column is used.
>
> On Sun, Sep 2, 2018 at 2:02 AM eugene miretsky <
> eugene.miret...@gmail.com> wrote:
>
>> Hello,
>>
>> Schema:
>>
>>-
>>
>>PUBLIC.GATABLE2.CUSTOMER_ID
>>
>>PUBLIC.GATABLE2.DT
>>
>>PUBLIC.GATABLE2.CATEGORY_ID
>>
>>PUBLIC.GATABLE2.VERTICAL_ID
>>
>>PUBLIC.GATABLE2.SERVICE
>>
>>PUBLIC.GATABLE2.PRODUCT_VIEWS_APP
>>
>>PUBLIC.GATABLE2.PRODUCT_CLICKS_APP
>>
>>PUBLIC.GATABLE2.PRODUCT_VIEWS_WEB
>>
>>PUBLIC.GATABLE2.PRODUCT_CLICKS_WEB
>>
>>PUBLIC.GATABLE2.PDP_SESSIONS_APP
>>
>>PUBLIC.GATABLE2.PDP_SESSIONS_WEB
>>- pkey = customer_id,dt
>>- affinityKey = customer
>>
>> Query:
>>
>>- select COUNT(*) FROM( Select customer_id from GATABLE2 where
>>category_id in (175925, 101450, 9005, 175930, 175930, 
>> 175940,175945,101450,
>>6453) group by customer_id having SUM(product_views_app) > 2 OR
>>SUM(product_clicks_app) > 1 )
>>
>> The table has 600M rows.
>> At first, the query took 1m, when we added an index on category_id
>> the query started taking 3m.
>>
>> The SQL execution plan for both queries is attached.
>>
>> We are using a single x1.16xlarge insntace with query parallelism
>> set to 32
>>
>> Cheers,
>> Eugene
>>
>>
>
> --
> Best regards,
> Andrey V. Mashenkov
>



Re: Query 3x slower with index

2018-09-17 Thread Ilya Kasnacheev
Hello!

Why don't you diff the results of those two queries, tell us what the
difference is?

Regards,
-- 
Ilya Kasnacheev


пн, 17 сент. 2018 г. в 16:08, eugene miretsky :

> Hello,
>
> Just wanted to see if anybody had time to look into this.
>
> Cheers,
> Eugene
>
> On Wed, Sep 12, 2018 at 6:29 PM eugene miretsky 
> wrote:
>
>> Thanks!
>>
>> Tried joining with an inlined table instead of IN as per the second
>> suggestion, and it didn't quite work.
>>
>> Query1:
>>
>>- Select COUNT(*) FROM( Select customer_id from GATABLE3  use Index(
>>) where category_id in (9005, 175930, 175930, 175940,175945,101450, 6453)
>>group by customer_id having SUM(product_views_app) > 2 OR
>>SUM(product_clicks_app) > 1 )
>>- exec time = 17s
>>- *Result: 3105868*
>>- Same exec time if using AFFINITY_KEY index or "_key_PK_hash or
>>customer_id index
>>- Using an index on category_id increases the query time 33s
>>
>> Query2:
>>
>>- Select COUNT(*) FROM( Select customer_id from GATABLE3 ga  use
>>index (PUBLIC."_key_PK") inner join table(category_id int = (9005, 175930,
>>175930, 175940,175945,101450, 6453)) cats on cats.category_id =
>>ga.category_id   group by customer_id having SUM(product_views_app) > 2 OR
>>SUM(product_clicks_app) > 1 )
>>- exec time = 38s
>>- *Result: 3113921*
>>- Same exec time if using AFFINITY_KEY index or "_key_PK_hash or
>>customer_id index or category_id index
>>- Using an index on category_id doesnt change the run time
>>
>> Query plans are attached.
>>
>> 3 questions:
>>
>>1. Why is the result differnt for the 2 queries - this is quite
>>concerning.
>>2. Why is the 2nd query taking longer
>>3. Why  category_id index doesn't work in case of query 2.
>>
>>
>> On Wed, Sep 5, 2018 at 8:31 AM Ilya Kasnacheev 
>> wrote:
>>
>>> Hello!
>>>
>>> I don't think that we're able to use index with IN () clauses. Please
>>> convert it into OR clauses.
>>>
>>> Please see
>>> https://apacheignite-sql.readme.io/docs/performance-and-debugging#section-sql-performance-and-usability-considerations
>>>
>>> Regards,
>>> --
>>> Ilya Kasnacheev
>>>
>>>
>>> пн, 3 сент. 2018 г. в 12:46, Andrey Mashenkov <
>>> andrey.mashen...@gmail.com>:
>>>
 Hi

 Actually, first query uses index on affinity key which looks more
 efficient than index on category_id column.
 The first query can process groups one by one and stream partial
 results from map phase to reduce phase as it use sorted index lookup,
 while second query should process full dataset on map phase before pass
 it for reducing.

 Try to use composite index (customer_id, category_id).

 Also, SqlQueryFields.setCollocated(true) flag can help Ignite to build
 more efficient plan when group by on collocated column is used.

 On Sun, Sep 2, 2018 at 2:02 AM eugene miretsky <
 eugene.miret...@gmail.com> wrote:

> Hello,
>
> Schema:
>
>-
>
>PUBLIC.GATABLE2.CUSTOMER_ID
>
>PUBLIC.GATABLE2.DT
>
>PUBLIC.GATABLE2.CATEGORY_ID
>
>PUBLIC.GATABLE2.VERTICAL_ID
>
>PUBLIC.GATABLE2.SERVICE
>
>PUBLIC.GATABLE2.PRODUCT_VIEWS_APP
>
>PUBLIC.GATABLE2.PRODUCT_CLICKS_APP
>
>PUBLIC.GATABLE2.PRODUCT_VIEWS_WEB
>
>PUBLIC.GATABLE2.PRODUCT_CLICKS_WEB
>
>PUBLIC.GATABLE2.PDP_SESSIONS_APP
>
>PUBLIC.GATABLE2.PDP_SESSIONS_WEB
>- pkey = customer_id,dt
>- affinityKey = customer
>
> Query:
>
>- select COUNT(*) FROM( Select customer_id from GATABLE2 where
>category_id in (175925, 101450, 9005, 175930, 175930, 
> 175940,175945,101450,
>6453) group by customer_id having SUM(product_views_app) > 2 OR
>SUM(product_clicks_app) > 1 )
>
> The table has 600M rows.
> At first, the query took 1m, when we added an index on category_id the
> query started taking 3m.
>
> The SQL execution plan for both queries is attached.
>
> We are using a single x1.16xlarge insntace with query parallelism set
> to 32
>
> Cheers,
> Eugene
>
>

 --
 Best regards,
 Andrey V. Mashenkov

>>>


Re: Query 3x slower with index

2018-09-17 Thread eugene miretsky
Hello,

Just wanted to see if anybody had time to look into this.

Cheers,
Eugene

On Wed, Sep 12, 2018 at 6:29 PM eugene miretsky 
wrote:

> Thanks!
>
> Tried joining with an inlined table instead of IN as per the second
> suggestion, and it didn't quite work.
>
> Query1:
>
>- Select COUNT(*) FROM( Select customer_id from GATABLE3  use Index( )
>where category_id in (9005, 175930, 175930, 175940,175945,101450, 6453)
>group by customer_id having SUM(product_views_app) > 2 OR
>SUM(product_clicks_app) > 1 )
>- exec time = 17s
>- *Result: 3105868*
>- Same exec time if using AFFINITY_KEY index or "_key_PK_hash or
>customer_id index
>- Using an index on category_id increases the query time 33s
>
> Query2:
>
>- Select COUNT(*) FROM( Select customer_id from GATABLE3 ga  use index
>(PUBLIC."_key_PK") inner join table(category_id int = (9005, 175930,
>175930, 175940,175945,101450, 6453)) cats on cats.category_id =
>ga.category_id   group by customer_id having SUM(product_views_app) > 2 OR
>SUM(product_clicks_app) > 1 )
>- exec time = 38s
>- *Result: 3113921*
>- Same exec time if using AFFINITY_KEY index or "_key_PK_hash or
>customer_id index or category_id index
>- Using an index on category_id doesnt change the run time
>
> Query plans are attached.
>
> 3 questions:
>
>1. Why is the result differnt for the 2 queries - this is quite
>concerning.
>2. Why is the 2nd query taking longer
>3. Why  category_id index doesn't work in case of query 2.
>
>
> On Wed, Sep 5, 2018 at 8:31 AM Ilya Kasnacheev 
> wrote:
>
>> Hello!
>>
>> I don't think that we're able to use index with IN () clauses. Please
>> convert it into OR clauses.
>>
>> Please see
>> https://apacheignite-sql.readme.io/docs/performance-and-debugging#section-sql-performance-and-usability-considerations
>>
>> Regards,
>> --
>> Ilya Kasnacheev
>>
>>
>> пн, 3 сент. 2018 г. в 12:46, Andrey Mashenkov > >:
>>
>>> Hi
>>>
>>> Actually, first query uses index on affinity key which looks more
>>> efficient than index on category_id column.
>>> The first query can process groups one by one and stream partial results
>>> from map phase to reduce phase as it use sorted index lookup,
>>> while second query should process full dataset on map phase before pass
>>> it for reducing.
>>>
>>> Try to use composite index (customer_id, category_id).
>>>
>>> Also, SqlQueryFields.setCollocated(true) flag can help Ignite to build
>>> more efficient plan when group by on collocated column is used.
>>>
>>> On Sun, Sep 2, 2018 at 2:02 AM eugene miretsky <
>>> eugene.miret...@gmail.com> wrote:
>>>
 Hello,

 Schema:

-

PUBLIC.GATABLE2.CUSTOMER_ID

PUBLIC.GATABLE2.DT

PUBLIC.GATABLE2.CATEGORY_ID

PUBLIC.GATABLE2.VERTICAL_ID

PUBLIC.GATABLE2.SERVICE

PUBLIC.GATABLE2.PRODUCT_VIEWS_APP

PUBLIC.GATABLE2.PRODUCT_CLICKS_APP

PUBLIC.GATABLE2.PRODUCT_VIEWS_WEB

PUBLIC.GATABLE2.PRODUCT_CLICKS_WEB

PUBLIC.GATABLE2.PDP_SESSIONS_APP

PUBLIC.GATABLE2.PDP_SESSIONS_WEB
- pkey = customer_id,dt
- affinityKey = customer

 Query:

- select COUNT(*) FROM( Select customer_id from GATABLE2 where
category_id in (175925, 101450, 9005, 175930, 175930, 
 175940,175945,101450,
6453) group by customer_id having SUM(product_views_app) > 2 OR
SUM(product_clicks_app) > 1 )

 The table has 600M rows.
 At first, the query took 1m, when we added an index on category_id the
 query started taking 3m.

 The SQL execution plan for both queries is attached.

 We are using a single x1.16xlarge insntace with query parallelism set
 to 32

 Cheers,
 Eugene


>>>
>>> --
>>> Best regards,
>>> Andrey V. Mashenkov
>>>
>>


Re: Query 3x slower with index

2018-09-12 Thread eugene miretsky
Thanks!

Tried joining with an inlined table instead of IN as per the second
suggestion, and it didn't quite work.

Query1:

   - Select COUNT(*) FROM( Select customer_id from GATABLE3  use Index( )
   where category_id in (9005, 175930, 175930, 175940,175945,101450, 6453)
   group by customer_id having SUM(product_views_app) > 2 OR
   SUM(product_clicks_app) > 1 )
   - exec time = 17s
   - *Result: 3105868*
   - Same exec time if using AFFINITY_KEY index or "_key_PK_hash or
   customer_id index
   - Using an index on category_id increases the query time 33s

Query2:

   - Select COUNT(*) FROM( Select customer_id from GATABLE3 ga  use index
   (PUBLIC."_key_PK") inner join table(category_id int = (9005, 175930,
   175930, 175940,175945,101450, 6453)) cats on cats.category_id =
   ga.category_id   group by customer_id having SUM(product_views_app) > 2 OR
   SUM(product_clicks_app) > 1 )
   - exec time = 38s
   - *Result: 3113921*
   - Same exec time if using AFFINITY_KEY index or "_key_PK_hash or
   customer_id index or category_id index
   - Using an index on category_id doesnt change the run time

Query plans are attached.

3 questions:

   1. Why is the result differnt for the 2 queries - this is quite
   concerning.
   2. Why is the 2nd query taking longer
   3. Why  category_id index doesn't work in case of query 2.


On Wed, Sep 5, 2018 at 8:31 AM Ilya Kasnacheev 
wrote:

> Hello!
>
> I don't think that we're able to use index with IN () clauses. Please
> convert it into OR clauses.
>
> Please see
> https://apacheignite-sql.readme.io/docs/performance-and-debugging#section-sql-performance-and-usability-considerations
>
> Regards,
> --
> Ilya Kasnacheev
>
>
> пн, 3 сент. 2018 г. в 12:46, Andrey Mashenkov  >:
>
>> Hi
>>
>> Actually, first query uses index on affinity key which looks more
>> efficient than index on category_id column.
>> The first query can process groups one by one and stream partial results
>> from map phase to reduce phase as it use sorted index lookup,
>> while second query should process full dataset on map phase before pass
>> it for reducing.
>>
>> Try to use composite index (customer_id, category_id).
>>
>> Also, SqlQueryFields.setCollocated(true) flag can help Ignite to build
>> more efficient plan when group by on collocated column is used.
>>
>> On Sun, Sep 2, 2018 at 2:02 AM eugene miretsky 
>> wrote:
>>
>>> Hello,
>>>
>>> Schema:
>>>
>>>-
>>>
>>>PUBLIC.GATABLE2.CUSTOMER_ID
>>>
>>>PUBLIC.GATABLE2.DT
>>>
>>>PUBLIC.GATABLE2.CATEGORY_ID
>>>
>>>PUBLIC.GATABLE2.VERTICAL_ID
>>>
>>>PUBLIC.GATABLE2.SERVICE
>>>
>>>PUBLIC.GATABLE2.PRODUCT_VIEWS_APP
>>>
>>>PUBLIC.GATABLE2.PRODUCT_CLICKS_APP
>>>
>>>PUBLIC.GATABLE2.PRODUCT_VIEWS_WEB
>>>
>>>PUBLIC.GATABLE2.PRODUCT_CLICKS_WEB
>>>
>>>PUBLIC.GATABLE2.PDP_SESSIONS_APP
>>>
>>>PUBLIC.GATABLE2.PDP_SESSIONS_WEB
>>>- pkey = customer_id,dt
>>>- affinityKey = customer
>>>
>>> Query:
>>>
>>>- select COUNT(*) FROM( Select customer_id from GATABLE2 where
>>>category_id in (175925, 101450, 9005, 175930, 175930, 
>>> 175940,175945,101450,
>>>6453) group by customer_id having SUM(product_views_app) > 2 OR
>>>SUM(product_clicks_app) > 1 )
>>>
>>> The table has 600M rows.
>>> At first, the query took 1m, when we added an index on category_id the
>>> query started taking 3m.
>>>
>>> The SQL execution plan for both queries is attached.
>>>
>>> We are using a single x1.16xlarge insntace with query parallelism set
>>> to 32
>>>
>>> Cheers,
>>> Eugene
>>>
>>>
>>
>> --
>> Best regards,
>> Andrey V. Mashenkov
>>
>


Query1_pKeyIdx
Description: Binary data


Query1_categoryIdIdx
Description: Binary data


Query2_categoryIdx
Description: Binary data


Query2_pKeyIdx
Description: Binary data


Re: Query 3x slower with index

2018-09-05 Thread Ilya Kasnacheev
Hello!

I don't think that we're able to use index with IN () clauses. Please
convert it into OR clauses.

Please see
https://apacheignite-sql.readme.io/docs/performance-and-debugging#section-sql-performance-and-usability-considerations

Regards,
-- 
Ilya Kasnacheev


пн, 3 сент. 2018 г. в 12:46, Andrey Mashenkov :

> Hi
>
> Actually, first query uses index on affinity key which looks more
> efficient than index on category_id column.
> The first query can process groups one by one and stream partial results
> from map phase to reduce phase as it use sorted index lookup,
> while second query should process full dataset on map phase before pass it
> for reducing.
>
> Try to use composite index (customer_id, category_id).
>
> Also, SqlQueryFields.setCollocated(true) flag can help Ignite to build
> more efficient plan when group by on collocated column is used.
>
> On Sun, Sep 2, 2018 at 2:02 AM eugene miretsky 
> wrote:
>
>> Hello,
>>
>> Schema:
>>
>>-
>>
>>PUBLIC.GATABLE2.CUSTOMER_ID
>>
>>PUBLIC.GATABLE2.DT
>>
>>PUBLIC.GATABLE2.CATEGORY_ID
>>
>>PUBLIC.GATABLE2.VERTICAL_ID
>>
>>PUBLIC.GATABLE2.SERVICE
>>
>>PUBLIC.GATABLE2.PRODUCT_VIEWS_APP
>>
>>PUBLIC.GATABLE2.PRODUCT_CLICKS_APP
>>
>>PUBLIC.GATABLE2.PRODUCT_VIEWS_WEB
>>
>>PUBLIC.GATABLE2.PRODUCT_CLICKS_WEB
>>
>>PUBLIC.GATABLE2.PDP_SESSIONS_APP
>>
>>PUBLIC.GATABLE2.PDP_SESSIONS_WEB
>>- pkey = customer_id,dt
>>- affinityKey = customer
>>
>> Query:
>>
>>- select COUNT(*) FROM( Select customer_id from GATABLE2 where
>>category_id in (175925, 101450, 9005, 175930, 175930, 
>> 175940,175945,101450,
>>6453) group by customer_id having SUM(product_views_app) > 2 OR
>>SUM(product_clicks_app) > 1 )
>>
>> The table has 600M rows.
>> At first, the query took 1m, when we added an index on category_id the
>> query started taking 3m.
>>
>> The SQL execution plan for both queries is attached.
>>
>> We are using a single x1.16xlarge insntace with query parallelism set to
>> 32
>>
>> Cheers,
>> Eugene
>>
>>
>
> --
> Best regards,
> Andrey V. Mashenkov
>


Re: Query 3x slower with index

2018-09-03 Thread Andrey Mashenkov
Hi

Actually, first query uses index on affinity key which looks more efficient
than index on category_id column.
The first query can process groups one by one and stream partial results
from map phase to reduce phase as it use sorted index lookup,
while second query should process full dataset on map phase before pass it
for reducing.

Try to use composite index (customer_id, category_id).

Also, SqlQueryFields.setCollocated(true) flag can help Ignite to build more
efficient plan when group by on collocated column is used.

On Sun, Sep 2, 2018 at 2:02 AM eugene miretsky 
wrote:

> Hello,
>
> Schema:
>
>-
>
>PUBLIC.GATABLE2.CUSTOMER_ID
>
>PUBLIC.GATABLE2.DT
>
>PUBLIC.GATABLE2.CATEGORY_ID
>
>PUBLIC.GATABLE2.VERTICAL_ID
>
>PUBLIC.GATABLE2.SERVICE
>
>PUBLIC.GATABLE2.PRODUCT_VIEWS_APP
>
>PUBLIC.GATABLE2.PRODUCT_CLICKS_APP
>
>PUBLIC.GATABLE2.PRODUCT_VIEWS_WEB
>
>PUBLIC.GATABLE2.PRODUCT_CLICKS_WEB
>
>PUBLIC.GATABLE2.PDP_SESSIONS_APP
>
>PUBLIC.GATABLE2.PDP_SESSIONS_WEB
>- pkey = customer_id,dt
>- affinityKey = customer
>
> Query:
>
>- select COUNT(*) FROM( Select customer_id from GATABLE2 where
>category_id in (175925, 101450, 9005, 175930, 175930, 175940,175945,101450,
>6453) group by customer_id having SUM(product_views_app) > 2 OR
>SUM(product_clicks_app) > 1 )
>
> The table has 600M rows.
> At first, the query took 1m, when we added an index on category_id the
> query started taking 3m.
>
> The SQL execution plan for both queries is attached.
>
> We are using a single x1.16xlarge insntace with query parallelism set to
> 32
>
> Cheers,
> Eugene
>
>

-- 
Best regards,
Andrey V. Mashenkov


Query 3x slower with index

2018-09-01 Thread eugene miretsky
Hello,

Schema:

   -

   PUBLIC.GATABLE2.CUSTOMER_ID

   PUBLIC.GATABLE2.DT

   PUBLIC.GATABLE2.CATEGORY_ID

   PUBLIC.GATABLE2.VERTICAL_ID

   PUBLIC.GATABLE2.SERVICE

   PUBLIC.GATABLE2.PRODUCT_VIEWS_APP

   PUBLIC.GATABLE2.PRODUCT_CLICKS_APP

   PUBLIC.GATABLE2.PRODUCT_VIEWS_WEB

   PUBLIC.GATABLE2.PRODUCT_CLICKS_WEB

   PUBLIC.GATABLE2.PDP_SESSIONS_APP

   PUBLIC.GATABLE2.PDP_SESSIONS_WEB
   - pkey = customer_id,dt
   - affinityKey = customer

Query:

   - select COUNT(*) FROM( Select customer_id from GATABLE2 where
   category_id in (175925, 101450, 9005, 175930, 175930, 175940,175945,101450,
   6453) group by customer_id having SUM(product_views_app) > 2 OR
   SUM(product_clicks_app) > 1 )

The table has 600M rows.
At first, the query took 1m, when we added an index on category_id the
query started taking 3m.

The SQL execution plan for both queries is attached.

We are using a single x1.16xlarge insntace with query parallelism set to 32

Cheers,
Eugene


QueryWithoutIndex
Description: Binary data


QueryWithIndex
Description: Binary data