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https://issues.apache.org/jira/browse/HIVE-13306?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Teddy Choi updated HIVE-13306:
------------------------------
Attachment: HIVE-13306.1.patch
It's a working draft. It shows 70x addition performance, 3x multiplication and
2x division performance regarding to existing implementations. I will modify
this code further for wider use cases and more performance and more
readability. Thanks. :)
{noformat}
# Run complete. Total time: 00:02:30
Benchmark
Mode Samples Score Error Units
o.a.h.b.v.VectorizedArithmeticBench.DecimalColAddDecimalColColumnBench.bench
avgt 2 4012665235.500 ± NaN ns/op
o.a.h.b.v.VectorizedArithmeticBench.DecimalColDivideDecimalColColumnBench.bench
avgt 2 19167315269.000 ± NaN ns/op
o.a.h.b.v.VectorizedArithmeticBench.DecimalColMultiplyDecimalColColumnBench.bench
avgt 2 3391096996.500 ± NaN ns/op
o.a.h.b.v.VectorizedArithmeticBench.DecimalV2ColAddDecimalColColumnBench.bench
avgt 2 56848247.500 ± NaN ns/op
o.a.h.b.v.VectorizedArithmeticBench.DecimalV2ColDivideDecimalColColumnBench.bench
avgt 2 9162374089.500 ± NaN ns/op
o.a.h.b.v.VectorizedArithmeticBench.DecimalV2ColMultiplyDecimalColColumnBench.bench
avgt 2 1146261770.500 ± NaN ns/op
{noformat}
> Better Decimal vectorization
> ----------------------------
>
> Key: HIVE-13306
> URL: https://issues.apache.org/jira/browse/HIVE-13306
> Project: Hive
> Issue Type: Bug
> Components: Hive
> Reporter: Matt McCline
> Assignee: Teddy Choi
> Priority: Critical
> Attachments: HIVE-13306.1.patch
>
>
> Decimal Vectorization Requirements
> • Today, the LongColumnVector, DoubleColumnVector, BytesColumnVector,
> TimestampColumnVector classes store the data as primitive Java data types
> long, double, or byte arrays for efficiency.
> • DecimalColumnVector is different - it has an array of Object references
> to HiveDecimal objects.
> • The HiveDecimal object uses an internal object BigDecimal for its
> implementation. Further, BigDecimal itself uses an internal object
> BigInteger for its implementation, and BigInteger uses an int array. 4
> objects total.
> • And, HiveDecimal is an immutable object which means arithmetic and
> other operations produce new HiveDecimal object with 3 new objects underneath.
> • A major reason Vectorization is fast is the ColumnVector classes except
> DecimalColumnVector do not have to allocate additional memory per row. This
> avoids memory fragmentation and pressure on the Java Garbage Collector that
> DecimalColumnVector can generate. It is very significant.
> • What can be done with DecimalColumnVector to make it much more
> efficient?
> o Design several new decimal classes that allow the caller to manage the
> decimal storage.
> o If it takes N int values to store a decimal (e.g. N=1..5), then a new
> DecimalColumnVector would have an int[] of length N*1024 (where 1024 is the
> default column vector size).
> o Why store a decimal in separate int values?
> • Java does not support 128 bit integers.
> • Java does not support unsigned integers.
> • In order to do multiplication of a decimal represented in a long you
> need twice the storage (i.e. 128 bits). So you need to represent parts in 32
> bit integers.
> • But really since we do not have unsigned, really you can only do
> multiplications on N-1 bits or 31 bits.
> • So, 5 ints are needed for decimal storage... of 38 digits.
> o It makes sense to have just one algorithm for decimals rather than one
> for HiveDecimal and another for DecimalColumnVector. So, make HiveDecimal
> store N int values, too.
> o A lower level primitive decimal class would accept decimals stored as
> int arrays and produces results into int arrays. It would be used by
> HiveDecimal and DecimalColumnVector.
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