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Further to the performance discussion @alamb - the StringBuilder pattern you suggested in https://github.com/apache/datafusion/pull/11136#discussion_r1657725214 does seem to materially improve performance:
#11279
Further to the performance discussion @alamb - the StringBuilder pattern you suggested in https://github.com/apache/datafusion/pull/11136#discussion_r1657725214 does seem to materially improve performance:
Extract data page statistics for String/extract_statistics/String
time: [15.368 µs 15.405 µs 15.446 µs]
change: [-68.672% -68.540% -68.409%] (p = 0.00 < 0.05)
Performance has improved.
Found 4 outliers among 100 measurements (4.00%)
4 (4.00%) high mild
So seems like a worthwhile thing to go ahead with? I think there are several places where we can do something similar.
One question - I notice in that ticket that you appended nulls for missing values. However, I think in most cases, missing values are simply omitted because all the None values are removed by flattening. So, in general, users of the data page statistics will need to check whether or not the length of the array matches the number of actual data pages? This is different from how the row group statistics are handled - they will instead have a null value for any missing statistics.
Is this difference in behaviour expected or just a side effect of the implementation.
So seems like a worthwhile thing to go ahead with? I think there are several places where we can do something similar.
One question - I notice in that ticket that you appended nulls for missing values. However, I think in most cases, missing values are simply omitted because all the None values are removed by flattening. So, in general, users of the data page statistics will need to check whether or not the length of the array matches the number of actual data pages? This is different from how the row group statistics are handled - they will instead have a null value for any missing statistics.
Is this difference in behaviour expected or just a side effect of the implementation.
Originally posted by @efredine in #10922 (comment)
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