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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2022/08/16 10:56:40 UTC
[GitHub] [spark] beliefer opened a new pull request, #37536: [WIP][SPARK-40100][SQL] Add DataType class for Int128 type
beliefer opened a new pull request, #37536:
URL: https://github.com/apache/spark/pull/37536
### What changes were proposed in this pull request?
Extend Catalyst's type system by a new type: Int128Type represents the Int128.
### Why are the changes needed?
Spark SQL today supports the Decimal data type. The implementation of Spark Decimal holds a BigDecimal or Long value. Spark Decimal provides some operators like +, -, *, /, % and so on. These operators rely heavily on the computational power of BigDecimal or Long itself. For ease of understanding, take the + as an example. The implementation shows below.
```
def + (that: Decimal): Decimal = {
if (decimalVal.eq(null) && that.decimalVal.eq(null) && scale == that.scale) {
Decimal(longVal + that.longVal, Math.max(precision, that.precision) + 1, scale)
} else {
Decimal(toBigDecimal.bigDecimal.add(that.toBigDecimal.bigDecimal))
}
}
```
We can see the + of Long will be called if Spark Decimal holds a Long value. Otherwise, the add of BigDecimal will be called if Spark Decimal holds a BigDecimal value. The other operators of Spark Decimal adopt the similar way. Furthermore, the code shown above calls Decimal.apply to construct a new instance of Spark Decimal. As we know, the add operator of BigDecimal constructed a new instance of BigDecimal. So, if we call the + operator of Spark Decimal who holds a Long value, Spark will construct a new instance of `Decimal`. Otherwise, Spark will construct a new instance of BigDecimal and a new instance of Decimal.
Through rough analysis, we know:
1. The computational power of Spark Decimal may depend on BigDecimal.
2. The calculation operators of Spark Decimal create a lot of new instances of Decimal and may create a lot of new instances of BigDecimal.
If a large table has a field called 'colA whose type is Spark Decimal, the execution of SUM('colA) will involve the creation of a large number of Spark Decimal instances and BigDecimal instances. These Spark Decimal instances and BigDecimal instances will lead to garbage collection frequently.
In this new feature, we will introduce Int128 type.
`Int128` is a high-performance data type about 2X~10X more efficient than Spark Decimal for typical operations. It uses a finite (128 bit) precision and can handle up to decimal(38, X). The implementation of Int128 just uses two Long values to represent the high and low bits of 128 bits respectively. Int128 is lighter than Spark `Decimal`, reduces the cost of new() and garbage collection.
This is a starting PR. See more details in https://issues.apache.org/jira/browse/SPARK-40097
### Does this PR introduce _any_ user-facing change?
No, a new data type for Int128. It is still in development.
### How was this patch tested?
New test cases.
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[GitHub] [spark] github-actions[bot] closed pull request #37536: [WIP][SPARK-40100][SQL] Add DataType class for Int128 type
Posted by GitBox <gi...@apache.org>.
github-actions[bot] closed pull request #37536: [WIP][SPARK-40100][SQL] Add DataType class for Int128 type
URL: https://github.com/apache/spark/pull/37536
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[GitHub] [spark] pkudinov commented on pull request #37536: [WIP][SPARK-40100][SQL] Add DataType class for Int128 type
Posted by GitBox <gi...@apache.org>.
pkudinov commented on PR #37536:
URL: https://github.com/apache/spark/pull/37536#issuecomment-1330178829
Hi @beliefer, are there any plans to complete this PR?
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[GitHub] [spark] github-actions[bot] commented on pull request #37536: [WIP][SPARK-40100][SQL] Add DataType class for Int128 type
Posted by GitBox <gi...@apache.org>.
github-actions[bot] commented on PR #37536:
URL: https://github.com/apache/spark/pull/37536#issuecomment-1328139474
We're closing this PR because it hasn't been updated in a while. This isn't a judgement on the merit of the PR in any way. It's just a way of keeping the PR queue manageable.
If you'd like to revive this PR, please reopen it and ask a committer to remove the Stale tag!
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