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https://issues.apache.org/jira/browse/PARQUET-2159?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17681551#comment-17681551
 ] 

ASF GitHub Bot commented on PARQUET-2159:
-----------------------------------------

jiangjiguang commented on code in PR #1011:
URL: https://github.com/apache/parquet-mr/pull/1011#discussion_r1089700107


##########
parquet-generator/src/main/java/org/apache/parquet/encoding/vectorbitpacking/BitPackingGeneratorVector.java:
##########
@@ -0,0 +1,63 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+package org.apache.parquet.encoding.vectorbitpacking;
+
+import java.io.*;
+
+/**
+ * This class generates vector bit packers that pack the most significant bit 
first.
+ * The result of the generation is checked in. To regenerate the code run this 
class and check in the result.
+ */
+public class BitPackingGeneratorVector {
+  private static final String CLASS_NAME_PREFIX_FOR_INT = 
"ByteBitPackingVector";
+  private static final String CLASS_NAME_PREFIX_FOR_LONG = 
"ByteBitPackingVectorForLong";
+
+  public static void main(String[] args) throws Exception {
+    String basePath = args[0];
+    //TODO: Int for Big Endian

Review Comment:
   OK, I will create JIRAs to  break down the work.





> Parquet bit-packing de/encode optimization
> ------------------------------------------
>
>                 Key: PARQUET-2159
>                 URL: https://issues.apache.org/jira/browse/PARQUET-2159
>             Project: Parquet
>          Issue Type: Improvement
>          Components: parquet-mr
>    Affects Versions: 1.13.0
>            Reporter: Fang-Xie
>            Assignee: Fang-Xie
>            Priority: Major
>             Fix For: 1.13.0
>
>         Attachments: image-2022-06-15-22-56-08-396.png, 
> image-2022-06-15-22-57-15-964.png, image-2022-06-15-22-58-01-442.png, 
> image-2022-06-15-22-58-40-704.png
>
>
> Current Spark use Parquet-mr as parquet reader/writer library, but the 
> built-in bit-packing en/decode is not efficient enough. 
> Our optimization for Parquet bit-packing en/decode with jdk.incubator.vector 
> in Open JDK18 brings prominent performance improvement.
> Due to Vector API is added to OpenJDK since 16, So this optimization request 
> JDK16 or higher.
> *Below are our test results*
> Functional test is based on open-source parquet-mr Bit-pack decoding 
> function: *_public final void unpack8Values(final byte[] in, final int inPos, 
> final int[] out, final int outPos)_* __
> compared with our implementation with vector API *_public final void 
> unpack8Values_vec(final byte[] in, final int inPos, final int[] out, final 
> int outPos)_*
> We tested 10 pairs (open source parquet bit unpacking vs ours optimized 
> vectorized SIMD implementation) decode function with bit 
> width=\{1,2,3,4,5,6,7,8,9,10}, below are test results:
> !image-2022-06-15-22-56-08-396.png|width=437,height=223!
> We integrated our bit-packing decode implementation into parquet-mr, tested 
> the parquet batch reader ability from Spark VectorizedParquetRecordReader 
> which get parquet column data by the batch way. We construct parquet file 
> with different row count and column count, the column data type is Int32, the 
> maximum int value is 127 which satisfies bit pack encode with bit width=7,   
> the count of the row is from 10k to 100 million and the count of the column 
> is from 1 to 4.
> !image-2022-06-15-22-57-15-964.png|width=453,height=229!
> !image-2022-06-15-22-58-01-442.png|width=439,height=217!
> !image-2022-06-15-22-58-40-704.png|width=415,height=208!



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