It seems that epoll-shim can help to mitigate this issue without much code.
вт, 14 мар. 2023 г. в 21:11, Ivan Daschinsky <ivanda...@gmail.com>:
> Yep, it has been broken since the introduction of epoll in the network
> code. So kqueue support needs to be implemented.
>
> вт, 14 мар. 2023 г. в 19:22, Stephen Darlington <
> stephen.darling...@gridgain.com>:
>
>> Macs don’t have epoll, so it doesn’t compile currently.
>>
>> On 14 Mar 2023, at 16:02, Igor Sapego <isap...@apache.org> wrote:
>>
>> Unfortunately, we do not have Mac agents, so we can not detect when
>> compilation on Mac OS is broken, so yeah...
>>
>> Best Regards,
>> Igor
>>
>>
>> On Tue, Mar 14, 2023 at 2:48 PM Ivan Daschinsky <ivanda...@gmail.com>
>> wrote:
>>
>>> An ignite odbc driver works well on linux and windows OSes, but it seems
>>> that it is impossible to compile it on Mac OS.
>>>
>>> вт, 14 мар. 2023 г. в 14:47, Ivan Daschinsky <ivanda...@gmail.com>:
>>>
>>>> Hi, Dren!
>>>>
>>>> Unfortunatelly, pyignite doesn't have an efficient native serialization
>>>> library, whereas psycopg2 has (it is a thin wrapper around libpq).
>>>>
>>>> I would suggest two options:
>>>> 1. Reduce a default batch size like this : `client.sql("SELECT * FROM
>>>> TABLE", page_size=10)`. Default 1024 seems too big and parsing of such a
>>>> big response seems to be really slow.
>>>> 2. Use ignite odbc driver and pyodbc over it. Both of them work pretty
>>>> well.
>>>>
>>>> вт, 14 мар. 2023 г. в 14:10, Dren Butković <dren.butko...@gmail.com>:
>>>>
>>>>>
>>>>> Ignite and py client versions:
>>>>>
>>>>> - Apache Ignite 2.13.0
>>>>> - pyignite 0.5.2
>>>>>
>>>>> On Tue, Mar 14, 2023 at 11:46 AM Zhenya Stanilovsky via user <
>>>>> user@ignite.apache.org> wrote:
>>>>>
>>>>>> Hi, plz append ignite and py client versions.
>>>>>>
>>>>>>
>>>>>> Hi,
>>>>>>
>>>>>> I made a speed comparison of retrieving data from Apache Ignite using
>>>>>> several methods. All records are in one table, I did not use any WHERE
>>>>>> condition, only a SELECT * FROM TABLE XYZ LIMIT 20000.
>>>>>>
>>>>>> Test results are:
>>>>>> Apache Ignite
>>>>>>
>>>>>> - Apache Ignite REST API - 0.52 seconds
>>>>>> - JDBC - 4 seconds
>>>>>> - Python pyignite - 40 seconds !!!
>>>>>>
>>>>>> pseudocode in Python using pyignite:
>>>>>>
>>>>>> client = Client(username="ignite", password="pass", use_ssl=False)
>>>>>> client.connect('localhost', 10800)
>>>>>>
>>>>>> cursor=client.sql('SELECT * FROM TABLE_XYZ LIMIT 20000')for row in
>>>>>> cursor:
>>>>>> pass
>>>>>>
>>>>>> After that I made a speed comparison of retrieving data from
>>>>>> PostgreSQL using JDBC and psycopg2 Python package. SQL select is same,
>>>>>> SELECT * FROM TABLE XYZ LIMIT 20000
>>>>>> PostgreSQL
>>>>>>
>>>>>> - JDBC - 3 seconds
>>>>>> - Python psycopg2 using fetchall - 3 seconds
>>>>>> - Python psycopg2 using fetchone - 4 seconds
>>>>>>
>>>>>> pseudocode in Python using psycopg2:
>>>>>>
>>>>>> import psycopg2
>>>>>>
>>>>>> conn = psycopg2.connect(database=DB_NAME,
>>>>>> user=DB_USER,
>>>>>> password=DB_PASS,
>>>>>> host=DB_HOST,
>>>>>> port=DB_PORT)
>>>>>>
>>>>>> cur = conn.cursor()
>>>>>> cur.execute("SELECT * FROM TABLE_XYZ LIMIT 20000")
>>>>>> rows = cur.fetchall()for data in rows:
>>>>>> pass
>>>>>>
>>>>>> I can conclude that the pyignite implementation has much worse
>>>>>> performance compared to psycopg2 tests. The performance difference on
>>>>>> PostgreSQL between Java JDBC and Python psycopg2 is negligible.
>>>>>>
>>>>>> The performance difference on Apache Ignite between Java JDBC and
>>>>>> Python pyignite is very big.
>>>>>>
>>>>>> Please if someone can comment on the tests, did I do something wrong
>>>>>> or are these results expected? How can such large differences in
>>>>>> execution
>>>>>> times be explained? Do you have any suggestions to get better results
>>>>>> using
>>>>>> pyignite?
>>>>>> Thank you
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>
>>>>
>>>> --
>>>> Sincerely yours, Ivan Daschinskiy
>>>>
>>>
>>>
>>> --
>>> Sincerely yours, Ivan Daschinskiy
>>>
>>
>>
>
> --
> Sincerely yours, Ivan Daschinskiy
>
--
Sincerely yours, Ivan Daschinskiy
