[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
Github user kiszk commented on the issue: https://github.com/apache/spark/pull/18014 It is older one. Let me close this. Then, I will submit another PR very soon to do the same thing in different way. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
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[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
Github user kiszk commented on the issue: https://github.com/apache/spark/pull/18014 @cloud-fan Here is an implementation based on Option 2 only for simple data types (e.g. boolean, int, double, and so on). Used bulk-copy for array body in `putArray()`, and used [element-wise copy for null bit if `containsNull()` is true](https://github.com/apache/spark/pull/18014/files#diff-7738d15a778268fd8b5574e2c655a660R683) in `putArray()`. Do you have any comments/feedbacks? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
Github user cloud-fan commented on the issue: https://github.com/apache/spark/pull/18014 I think option 2 is better. `ColumnVector.getArray()` should be as fast as possible. The caller side may just get an element from this array and then the final projection doesn't need to copy an array. But if we do need to copy the array in the final projection, we should also speed it up by bulk copy. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
Github user kiszk commented on the issue:
https://github.com/apache/spark/pull/18014
@cloud-fan When I think about the use case of `ColumnVector.getArray` (i.e.
in generated code by the whole-stage code geneneration), I think that it is
better to return `UnsafeArrayData` instead of `ColumnVector.Array` in the
currnet generated code.
The following is an example program and current generated code. In the
generated code, we will replace `inputadapter_row.getArray(0)` at line 35 with
`columnVector.getArray(rowIdx)`. So, let us assume
`columnVector.getArray(rowIdx)` is used and focus on `inputadapter_value`.
At projection, if a type of `inputadapter_value` is `UnsafeArrayData`, line
72 just performs fast memory copy for a contigious region. On the other hand,
if a type of `inputadapter_value` is `ColumnVector.Array`, lines 79-86 performs
element-wise copy that is slower.
I think that there are three options.
1. Add a method `UnsafeArrayData ColumnVector.getArray()` to use
`UnsafeArrayData` anywhere in the generated code.
2. Add a conditional branch for `ColumnVector.Array` in the generated code
and prepare specialized copy routine for `ColumnVector.Array`. In this case, we
can use bulk copy for array body, but use element-wise copy for null bits.
3. In addition to 2, we support bit-wise null bits representation in
`ColumnVector.Array`. In this case, we can use two bulk copy. One is for null
bits, and the other is for array body. Downside of this approach is to
introduce additional conditional branch at ColumnVector.isNullAt() (i.e. check
whether we use byte-wise or bit-wise null representation).
What do you think? Or, are there any other ideas?
```java
val df = sparkContext.parallelize(Seq(Array(0, 1), Array(1, 2)),
1).toDF("a").cache
df.count
df.filter("a[0] > 0").show
```
```java
/* 031 */ protected void processNext() throws java.io.IOException {
/* 032 */ while (inputadapter_input.hasNext() && !stopEarly()) {
/* 033 */ InternalRow inputadapter_row = (InternalRow)
inputadapter_input.next();
/* 034 */ boolean inputadapter_isNull = inputadapter_row.isNullAt(0);
/* 035 */ ArrayData inputadapter_value = inputadapter_isNull ? null :
(inputadapter_row.getArray(0));
/* 037 */ if (!(!(inputadapter_isNull))) continue;
/* 039 */ boolean filter_isNull2 = true;
/* 040 */ boolean filter_value2 = false;
/* 042 */ boolean filter_isNull3 = true;
/* 043 */ int filter_value3 = -1;
/* 045 */ filter_isNull3 = false;
/* 047 */ final int filter_index = (int) 0;
/* 048 */ if (filter_index >= inputadapter_value.numElements() ||
filter_index < 0 || inputadapter_value.isNullAt(filter_index)) {
/* 049 */ filter_isNull3 = true;
/* 050 */ } else {
/* 051 */ filter_value3 = inputadapter_value.getInt(filter_index);
/* 052 */ }
/* 053 */ if (!filter_isNull3) {
/* 054 */ filter_isNull2 = false;
/* 055 */ filter_value2 = filter_value3 > 0;
/* 057 */ }
/* 058 */ if (filter_isNull2 || !filter_value2) continue;
/* 060 */ filter_numOutputRows.add(1);
/* 062 */ filter_holder.reset();
/* 066 */ final int filter_tmpCursor = filter_holder.cursor;
/* 068 */ if (inputadapter_value instanceof UnsafeArrayData) {
/* 069 */ final int filter_sizeInBytes = ((UnsafeArrayData)
inputadapter_value).getSizeInBytes();
/* 071 */ filter_holder.grow(filter_sizeInBytes);
/* 072 */ ((UnsafeArrayData)
inputadapter_value).writeToMemory(filter_holder.buffer, filter_holder.cursor);
/* 073 */ filter_holder.cursor += filter_sizeInBytes;
/* 075 */ } else {
/* 076 */ final int filter_numElements =
inputadapter_value.numElements();
/* 077 */ filter_arrayWriter.initialize(filter_holder,
filter_numElements, 4);
/* 079 */ for (int filter_index1 = 0; filter_index1 <
filter_numElements; filter_index1++) {
/* 080 */ if (inputadapter_value.isNullAt(filter_index1)) {
/* 081 */ filter_arrayWriter.setNullInt(filter_index1);
/* 082 */ } else {
/* 083 */ final int filter_element =
inputadapter_value.getInt(filter_index1);
/* 084 */ filter_arrayWriter.write(filter_index1,
filter_element);
/* 085 */ }
/* 086 */ }
/* 087 */ }
/* 089 */ filter_rowWriter.setOffsetAndSize(0, filter_tmpCursor,
filter_holder.cursor - filter_tmpCursor);
/* 090 */ filter_result.setTotalSize(filter_holder.totalSize());
/* 091 */ append(filter_result);
/* 092 */ if (shouldStop()) return;
/* 093 */ }
/* 094 */ }
```
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[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
Github user kiszk commented on the issue: https://github.com/apache/spark/pull/18014 Yes. Let me implement new `putArray(int rowId, Array array)` that uses `ColumnVector.Array` and stores primitive-type elements into a primitive array (e.g. `intData`). --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
Github user cloud-fan commented on the issue: https://github.com/apache/spark/pull/18014 I took a look at `ColumnVector.getArray`, seems it's already no cost? The writing needs some copy though. --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
Github user kiszk commented on the issue: https://github.com/apache/spark/pull/18014 @cloud-fan Thank you for your comments. Let me confirm your ideas. 1. Do you want to keep array contents in [a primitive data array (e.g. intData[])](https://github.com/apache/spark/blob/master/sql/core/src/main/java/org/apache/spark/sql/execution/vectorized/OnHeapColumnVector.java#L43) of `UnsafeArrayData`? 2. How do you want to update `UnsafeArrayData`? We can map the current `UnsafeArrayData` into `ColumnVector`. The following is the format of `UnsafeArrayData`. ``` [numElements][null bits][values or offset][variable length portion] ``` * numElements: store it into `arrayLengths[]` * [null bits]: ***Need to conversion from bitvector representation to byte representation*** * [values]: store as each data type * [offset][variable length portion]: store as `ByteType` The issue is for conversion of `null bits`. However, if we use byte representation in `UnsafeArrayData`, it may waste more memory space. To avoid this, we could update `ColumnVector` to support bitvector representation for nullability of each element. On the other hand, current my approach stores the whole `UnsafeArrayData` as a binary into [`byte[] data`](https://github.com/apache/spark/pull/18014/files#diff-f1e0f2d99a6cdc0113487f8358861fb3R56). The advantage of this approach is no cost for conversion at put/get. What do you think? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
Github user cloud-fan commented on the issue: https://github.com/apache/spark/pull/18014 I think there is a gap between columnar format and the unsafe row format. The current `ColumnVector` format looks reasonable for array type, as it puts the leaf elements together, which is better for compression. While changing it to binary makes it faster if we need to read an array from `ColumnVector` and convert it to `ArrayData`, it's really an efficient way to store arrays in columnar format. Shall we consider updating`UnsafeArrayData` format? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
Github user kiszk commented on the issue: https://github.com/apache/spark/pull/18014 @cloud-fan Could you please let us know your thoughts? Is it better to use binary type or to add simple logic for `UnsafeArrayData` and others in `ColumnVector`? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
Github user kiszk commented on the issue: https://github.com/apache/spark/pull/18014 @cloud-fan What would you think? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
Github user kiszk commented on the issue: https://github.com/apache/spark/pull/18014 I thought that idea is for Apache Arrow. We could use binary type for `UnsafeArrayData`. However, it involves some complexity to use [`ColumnVector.Array`](https://github.com/apache/spark/blob/master/sql/core/src/main/java/org/apache/spark/sql/execution/vectorized/ColumnVector.java#L1015-L1017). Is it better to use existing code? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
Github user cloud-fan commented on the issue: https://github.com/apache/spark/pull/18014 I may miss something, can we just treat array type as binary type and put it in `ColumnVector`? --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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Github user kiszk commented on the issue: https://github.com/apache/spark/pull/18014 @hvanhovell @sameeragarwal would it be possible to look at this? cc: @cloud-fan --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- - To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org
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[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
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[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
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[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
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[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
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[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
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[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
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[GitHub] spark issue #18014: [SPARK-20783][SQL] Enhance ColumnVector to keep UnsafeAr...
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