JFinis commented on code in PR #196:
URL: https://github.com/apache/parquet-format/pull/196#discussion_r1146076533
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README.md:
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@@ -163,18 +163,25 @@ following rules:
[Thrift definition](src/main/thrift/parquet.thrift) in the
`ColumnOrder` union. They are summarized here but the Thrift definition
is considered authoritative:
- * NaNs should not be written to min or max statistics fields.
- * If the computed max value is zero (whether negative or positive),
- `+0.0` should be written into the max statistics field.
- * If the computed min value is zero (whether negative or positive),
- `-0.0` should be written into the min statistics field.
-
- For backwards compatibility when reading files:
- * If the min is a NaN, it should be ignored.
- * If the max is a NaN, it should be ignored.
- * If the min is +0, the row group may contain -0 values as well.
- * If the max is -0, the row group may contain +0 values as well.
- * When looking for NaN values, min and max should be ignored.
+ * The following compatibility rules should be applied when reading
statistics:
+ * If the nan_count field is set to > 0 and both min and max are
Review Comment:
@mapleFU To your general comment (I can't answer there)
> The skeleton LGTM. But I wonder why if it has min/max/nan_count, it can
decide nan by min-max. Can we just decide it by `null_count + nan_count ==
num_values`?
The problem is that the ColumnIndex does not have the `num_values` field,
so using this computation to derive whether there are only NaNs would only be
applicable to Statistics, not to the column index. Of course, we could do what
I suggested in alternatives and give the column index a `num_values` list. Then
this would indeed work everywhere but at the cost of an additional list.
So I see we have the following options:
* Do what I did here, i.e., use min/max to determine whether there are only
NaNs
* Add a `num_values` list to the ColumnIndex
* Accept the fact that the column index cannot detect only-NaN pages (might
lead to fishy semantics)
* Tell readers to use the `min==max==NaN` reasoning only in the column
index, and use the `null_count + nan_count == num_values` for the statistics.
Which one would you suggest here?
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