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From Orhan Kislal <okis...@pivotal.io>
Subject Re: PostgreSQL crashed during random forest training
Date Wed, 24 Oct 2018 20:28:46 GMT
Hi Luyao Chen,

I was wondering if you are still experiencing this issue? If not, we will
close the JIRA. Otherwise, it would be helpful to add your system
information to the JIRA (OS, database and MADlib version).

Thanks,

Orhan Kislal


On Thu, Oct 18, 2018 at 10:59 AM Orhan Kislal <okislal@pivotal.io> wrote:

> Hi Luyao Chen,
>
> I started looking into this bug. Currently, I am running it on OSX 10.13,
> Postgres 10, MADlib 1.15.1 without issue. Could you share your system
> information? OS, database and MADlib version would be most helpful.
>
> Thanks,
>
> Orhan
>
> On Sat, Jul 28, 2018 at 2:28 PM Frank McQuillan <fmcquillan@pivotal.io>
> wrote:
>
>> thanks, I added this info to the jira
>>
>> On Fri, Jul 27, 2018 at 7:23 AM, LUYAO CHEN <luyao_chen@hotmail.com>
>> wrote:
>>
>>> The similar problem happened in decision tree.  ( with the same set of
>>> data ).
>>>
>>> I got the error (dmesg) that "
>>>  [ 4289.020198] postmaster[1840]: segfault at 0 ip 00007f17cd5f4ea3 sp
>>> 00007ffdf867dd50 error 4 in libmadlib.so[7f17cd2ec000+64a000]"
>>>
>>>
>>>
>>>
>>> Regards,
>>> Luyao Chen
>>>
>>> ------------------------------
>>> *From:* Frank McQuillan <fmcquillan@pivotal.io>
>>> *Sent:* Tuesday, July 24, 2018 2:13 PM
>>>
>>> *To:* user@madlib.apache.org
>>> *Subject:* Re: PostgreSQL crashed during random forest training
>>>
>>> Thank you, we created a JIRA to investigate this
>>> https://issues.apache.org/jira/browse/MADLIB-1257
>>>
>>> On Tue, Jul 24, 2018 at 10:31 AM, LUYAO CHEN <luyao_chen@hotmail.com>
>>> wrote:
>>>
>>> Another observation -  It crashed with 84 groups and 73K instance. In
>>> this scenario, I shall have pretty enough memory and disk.
>>>
>>> Also seems during the increasing of the groups, it used a lot of
>>> temporary disk space when the data is over certain groups.
>>>
>>>
>>> Regards,
>>>
>>> ------------------------------
>>> *From:* LUYAO CHEN <luyao_chen@hotmail.com>
>>> *Sent:* Tuesday, July 24, 2018 9:15 AM
>>> *To:* user@madlib.apache.org
>>> *Subject:* Re: PostgreSQL crashed during random forest training
>>>
>>>
>>> Hi Frank,
>>>
>>>
>>> You may refer to the enclosed dump data for the training table, and I
>>> used the below  SQL for random forest.
>>>
>>>
>>> DROP TABLE IF EXISTS train_output, train_output_group,
>>> train_output_summary;
>>> SELECT madlib.forest_train('train_data',         -- source table
>>>                            'train_output',    -- output model table
>>>                            'rowid',              -- id column
>>>                            'positive',           -- response
>>>                            'features',   -- features
>>>                            NULL,              -- exclude columns
>>>                            'caseid',              -- grouping columns
>>>                            30::integer,       -- number of trees
>>>                            30::integer,        -- number of random
>>> features
>>>                            TRUE::boolean,     -- variable importance
>>>                            1::integer,        -- num_permutations
>>>                            10::integer,        -- max depth
>>>                            3::integer,        -- min split
>>>                            1::integer,        -- min bucket
>>>                            10::integer,        -- number of splits per
>>> continuous variable
>>>                            NULL,         -- null handling parameter
>>>                            TRUE          --   verbose
>>>                            );
>>>
>>> Regards,
>>> Luyao Chen
>>>
>>> ------------------------------
>>> *From:* Frank McQuillan <fmcquillan@pivotal.io>
>>> *Sent:* Monday, July 23, 2018 4:59 PM
>>> *To:* user@madlib.apache.org
>>> *Subject:* Re: PostgreSQL crashed during random forest training
>>>
>>> Hi Luyao Chen
>>>
>>> It's hard to debug just looking at that trace.
>>>
>>> 1) If you increase your data size to more than 56K instances in 56
>>> groups, does it work?  e.g., double it to approx 112K instances and 112
>>> groups.
>>>
>>> 2) Is it possible of you could share a sample of your data so that we
>>> could try?  If not, perhaps anonymize a sample of the data so that we can
>>> multiply it out to make it bigger?  Then we could take a closer look.
>>>
>>> Frank
>>>
>>> On Mon, Jul 23, 2018 at 12:34 PM, LUYAO CHEN <luyao_chen@hotmail.com>
>>> wrote:
>>>
>>> Dear user group,
>>>
>>>
>>> I got a problem when training the grouped data with random forest(300
>>> features). Small data was fine ( eg, 56K instances in 56 groups), but
>>> failed for 240K instances in 250 groups. Postgres forced to disconnect the
>>> session after showing the below message in verbose mode:
>>>
>>>
>>> NOTICE:  view "__madlib_temp_60124179_1532371657_7130296__" will be a
>>> temporary view
>>> NOTICE:  sql_create_empty_result_table:
>>>
>>>             CREATE TABLE analysis.dx_rf_train_output_1 (
>>>                 gid         integer,
>>>                 sample_id   integer,
>>>                 tree        madlib.bytea8);
>>>
>>> NOTICE:  sql_refresh_training_pois_cnt:
>>>
>>>                             TRUNCATE TABLE
>>> __madlib_temp_91155016_1532371657_5660955__ CASCADE;
>>>                             INSERT INTO
>>> __madlib_temp_91155016_1532371657_5660955__
>>>                             SELECT
>>>                                 *,
>>>                                 madlib.poisson_random(1) AS poisson_count
>>>                             FROM
>>>                             (
>>>                                 SELECT
>>>                                     *,
>>>                                     0.::double precision AS
>>> __madlib_temp_14328459_1532371657_7318497__
>>>                                 FROM analysis.dxpredict_svec
>>>                             ) subq
>>>                             WHERE
>>> __madlib_temp_14328459_1532371657_7318497__ < 1
>>>
>>> NOTICE:
>>>                         src_cnt: 158360,
>>>                         oob_cnt: 92418,
>>>                         dup_cnt: 250617.
>>>
>>> NOTICE:  Started tree building for all groups
>>> server closed the connection unexpectedly
>>>         This probably means the server terminated abnormally
>>>         before or while processing the request.
>>> The connection to the server was lost. Attempting reset: Failed.
>>>
>>> The PostgreSQL did not capture the detail log even I increased the
>>> logstatement to "all"
>>> 2018-07-23 14:47:50.229 EDT [1090] LOG:  server process (PID 1980) was
>>> terminated by signal 11: Segmentation fault
>>> 2018-07-23 14:47:50.229 EDT [1090] DETAIL:  Failed process was running:
>>> SELECT madlib.forest_train('analysis.dxpredict_svec',
>>>                                    'analysis.dx_rf_train_output_1',
>>>                                    'rowid',
>>>                                    'positive',
>>>                                    '*',
>>>                                    'rowid,positive,case_icd',
>>>                                    'case_icd',
>>>                                    30::integer,
>>>                                    30::integer,
>>>                                    TRUE::boolean,
>>>                                    1::integer,
>>>                                    10::integer,
>>>                                    3::integer,
>>>                                    1::integer,
>>>                                    10::integer,
>>>                                    NULL,
>>>                                    TRUE
>>>                                    );
>>> 2018-07-23 14:47:50.229 EDT [1090] LOG:  terminating any other active
>>> server processes
>>> 2018-07-23 14:47:50.229 EDT [1401] WARNING:  terminating connection
>>> because of crash of another server process
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>

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