when loading the same data with the same query - it is overwriting the data in memory (changing the frame in memory) #7801
Comments
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Retima Dangol commented: [https://0xdata.atlassian.net/browse/PUBDEV-7840|https://0xdata.atlassian.net/browse/PUBDEV-7840|smart-link] It shouldn't be problem( or wouldn’t have noticed) if the data received as (fetch_mode = distributed | single) would have been same, as expected but they are not (jira above). |
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Ondrej Nekola commented: Base of the fix tested by [~accountid:5d1185d3912da30c634707cb] . The PR: [https://github.com//pull/5064|https://github.com//pull/5064|smart-link] |
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Ondrej Nekola commented: [~accountid:5d1185d3912da30c634707cb] It would be problem anyway, because the data would be overwriten even if they would come from a different database just with the same table name. Or from a different select from the same table (e.g. read {{id}} and {{name}} from {{users}} to {{frame1}} and then read {{id}} and {{rating}} to a {{frame2}} would rewrite {{frame1}}) |
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Ondrej Nekola commented: Fixed. |
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JIRA Issue Migration Info Jira Issue: PUBDEV-7841 Linked PRs from JIRA Attachments From Jira Attachment Name: image-2020-10-15-12-27-48-015.png Attachment Name: snowflakes_with_server (1).html |
when loading the same data with the same query - it is overwriting the data in memory (changing the frame in memory).
Example pseudo code:
on same instance and cluster
df1 = import_sql_select(table1, fetch_mode = “SINGLE”)
df2 = import_sql_select(table1, fetch_mode = “DISTRIBUTED”)
when referencing the parameters for df1 then it is returning the parameters of df2 ,,
since it has already overwritten the df1 info by df2's info
which means when I try to get parameters such as “max” or “min” of “df1” it is returning me the “min” and “max” of df2.
See the reference attachment.
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