[FIX] spreadsheet: batch process spreadsheet_revision.commands
#284
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Pirols
reviewed
Jun 11, 2025
src/util/spreadsheet/misc.py
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| def iter_commands(cr, like_all=(), like_any=()): | ||
| if not (bool(like_all) ^ bool(like_any)): | ||
| raise ValueError("Please specify `like_all` or `like_any`, not both") | ||
| cr.execute( | ||
| ncr = pg.named_cursor(cr, itersize=BATCH_SIZE) |
There was a problem hiding this comment.
Using a context manager you do not need to close it explicitely1.
Suggested change
| ncr = pg.named_cursor(cr, itersize=BATCH_SIZE) | |
| with pg.named_cursor(cr, itersize=BATCH_SIZE) as ncr: |
That said, this is just in the name of a more pythonic implementation. IOW: imo you can keep your current version, if you like it better.
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aj-fuentes
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src/util/spreadsheet/misc.py
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| SELECT id, | ||
| commands | ||
| FROM spreadsheet_revision | ||
| WHERE commands LIKE {}(%s::text[]) |
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Keep the formatting.
Suggested change
| SELECT id, | |
| commands | |
| FROM spreadsheet_revision | |
| WHERE commands LIKE {}(%s::text[]) | |
| SELECT id, | |
| commands | |
| FROM spreadsheet_revision | |
| WHERE commands LIKE {}(%s::text[]) |
src/util/spreadsheet/misc.py
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| if "commands" not in data_loaded: | ||
| continue | ||
| data_old = json.dumps(data_loaded, sort_keys=True) | ||
| with pg.named_cursor(cr, itersize=1) as ncr: |
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You can either leave the default itersize, or optimize the value to something that would work depending on the data. Another alternative is to use fetchmany directly.
Suggested change
| with pg.named_cursor(cr, itersize=1) as ncr: | |
| with pg.named_cursor(cr) as ncr: |
Some dbs have `spreadsheet_revision` records with over 10 millions characters in `commands`. If the number of record is high, this leads to memory errors. We distribute them in buckets of `memory_cap` maximum size, and use a named cursor to process them in buckets. Commands larger than `memory_cap` fit in one bucket.
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| start_bucket AS ( | ||
| SELECT 1 AS bucket | ||
| ), | ||
| ordered_rows AS ( | ||
| SELECT id, | ||
| LENGTH(commands) AS length, | ||
| ROW_NUMBER() OVER (ORDER BY LENGTH(commands), id) AS rownum | ||
| FROM spreadsheet_revision | ||
| WHERE commands LIKE {}(%s::text[]) | ||
| ), | ||
| assign AS ( | ||
| SELECT o.id AS id, | ||
| o.length, | ||
| o.rownum, | ||
| sb.bucket AS bucket, | ||
| o.length AS sum | ||
| FROM ordered_rows o, start_bucket sb | ||
| WHERE o.rownum = 1 | ||
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| UNION ALL | ||
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| SELECT o.id AS id, | ||
| o.length, | ||
| o.rownum, | ||
| CASE | ||
| WHEN a.sum + o.length > {memory_cap} THEN a.bucket + 1 | ||
| ELSE a.bucket | ||
| END AS bucket, | ||
| CASE | ||
| WHEN a.sum + o.length > {memory_cap} THEN o.length | ||
| ELSE a.sum + o.length | ||
| END AS sum | ||
| FROM assign a | ||
| JOIN ordered_rows o | ||
| ON o.rownum = a.rownum + 1 | ||
| ) | ||
| SELECT count(*),ARRAY_AGG(id) | ||
| FROM assign | ||
| GROUP BY bucket | ||
| ORDER BY bucket; |
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I think this can be simplified. You only need for each id the number of the bucket where it would be. In case one length is longer than one bucket you want to keep the record alone in it's bucket to avoid some smaller records making the group take even more space.
You can return the ids and commands already per bucket. That way you can iterate over the named cursor one by one.
Example query: (/!\warning: untested/!)
buckets AS (
SELECT id,
mod(SUM(length(commands) OVER (ORDER BY id), %(bucket_size)s) AS num,
length(commands) > %(bucket_size)s AS alone
FROM spreadsheet_revision
WHERE commands LIKE {}(%(filters)s::text[])
ORDER BY id
)
SELECT ARRAY_AGG(id ORDER BY id)
ARRAY_AGG(commands ORDER BY id)
FROM buckets
GROUP BY num, alonethen
for ids, datas in ncr: # you can iterate one by one here
for id, data in zip(ids, datas):
...
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[FIX] spreadsheet: batch process
spreadsheet_revision.commandsSome dbs have
spreadsheet_revisionrecords with over 10 millions characters incommands. If the number of record is high, this leads to memory errors here. We distribute them in buckets ofmemory_capmaximum size, and use a named cursor to process them in buckets. Commands larger thanmemory_capfit in one bucket.Fixes upg-2899961