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https://issues.apache.org/jira/browse/PARQUET-1866?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17123439#comment-17123439
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ASF GitHub Bot commented on PARQUET-1866:
-----------------------------------------
gszadovszky commented on a change in pull request #793:
URL: https://github.com/apache/parquet-mr/pull/793#discussion_r433675252
##########
File path:
parquet-hadoop/src/test/java/org/apache/parquet/hadoop/TestZstandardCodec.java
##########
@@ -0,0 +1,146 @@
+/*
+ * 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.hadoop;
+
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.fs.FileSystem;
+import org.apache.hadoop.fs.Path;
+import org.apache.hadoop.io.LongWritable;
+import org.apache.hadoop.io.Text;
+import org.apache.hadoop.io.compress.CompressionOutputStream;
+import org.apache.hadoop.mapred.JobClient;
+import org.apache.hadoop.mapred.JobConf;
+import org.apache.hadoop.mapred.OutputCollector;
+import org.apache.hadoop.mapred.Reporter;
+import org.apache.hadoop.mapred.RunningJob;
+import org.apache.hadoop.mapred.TextInputFormat;
+import org.apache.parquet.bytes.BytesInput;
+import org.apache.parquet.example.data.Group;
+import org.apache.parquet.example.data.simple.SimpleGroupFactory;
+import org.apache.parquet.hadoop.codec.ZstandardCodec;
+import org.apache.parquet.hadoop.example.GroupWriteSupport;
+import org.apache.parquet.hadoop.mapred.DeprecatedParquetOutputFormat;
+import org.apache.parquet.hadoop.metadata.CompressionCodecName;
+import org.apache.parquet.schema.MessageTypeParser;
+import org.junit.Assert;
+import org.junit.Test;
+
+import java.io.ByteArrayOutputStream;
+import java.io.IOException;
+import java.io.InputStream;
+import java.nio.file.Files;
+import java.util.Random;
+
+public class TestZstandardCodec {
+
+ private final Path inputPath = new
Path("src/test/java/org/apache/parquet/hadoop/example/TestInputOutputFormat.java");
+
+ @Test
+ public void testZstdCodec() throws IOException {
+ ZstandardCodec codec = new ZstandardCodec();
+ Configuration conf = new Configuration();
+ int[] levels = {1, 4, 7, 10, 13, 16, 19, 22};
+ int[] dataSizes = {0, 1, 10, 1024, 1024 * 1024};
+
+ for (int i = 0; i < levels.length; i++) {
+ conf.setInt(ZstandardCodec.PARQUET_COMPRESS_ZSTD_LEVEL, levels[i]);
+ codec.setConf(conf);
+ for (int j = 0; j < dataSizes.length; j++) {
+ testZstd(codec, dataSizes[j]);
+ }
+ }
+ }
+
+ private void testZstd(ZstandardCodec codec, int dataSize) throws IOException
{
+ byte[] data = new byte[dataSize];
+ (new Random()).nextBytes(data);
+ BytesInput compressedData = compress(codec, BytesInput.from(data));
+ BytesInput decompressedData = decompress(codec, compressedData,
data.length);
+ Assert.assertArrayEquals(data, decompressedData.toByteArray());
+ }
+
+ private BytesInput compress(ZstandardCodec codec, BytesInput bytes) throws
IOException {
+ ByteArrayOutputStream compressedOutBuffer = new
ByteArrayOutputStream((int)bytes.size());
+ CompressionOutputStream cos =
codec.createOutputStream(compressedOutBuffer, null);
+ bytes.writeAllTo(cos);
+ cos.close();
+ return BytesInput.from(compressedOutBuffer);
+ }
+
+ private BytesInput decompress(ZstandardCodec codec, BytesInput bytes, int
uncompressedSize) throws IOException {
+ BytesInput decompressed;
+ InputStream is = codec.createInputStream(bytes.toInputStream(), null);
+ decompressed = BytesInput.from(is, uncompressedSize);
+ is.close();
+ return decompressed;
+ }
+
+ @Test
+ public void testZstdConfWithMr() throws Exception {
+ JobConf jobConf = new JobConf();
+ Configuration conf = new Configuration();
+ jobConf.setInt(ZstandardCodec.PARQUET_COMPRESS_ZSTD_LEVEL, 18);
+ jobConf.setInt(ZstandardCodec.PARQUET_COMPRESS_ZSTD_LEVEL, 4);
+ RunningJob mapRedJob = runMapReduceJob(CompressionCodecName.ZSTD, jobConf,
conf);
+ assert(mapRedJob.isSuccessful());
+ }
+
+ private RunningJob runMapReduceJob(CompressionCodecName codec, JobConf
jobConf, Configuration conf) throws IOException, ClassNotFoundException,
InterruptedException {
Review comment:
Yes, I know, there is no 100% guarantee in normal circumstances. But if
you write the test in a deterministic way (as it should be by e.g. using a fix
seed for random generation) then without changing the data and the compression
codec it shall be fine. I worth a comment, though about it is not the nicest
way of testing the work of the properties but currently that's seems to be the
only one.
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> Replace Hadoop ZSTD with JNI-ZSTD
> ---------------------------------
>
> Key: PARQUET-1866
> URL: https://issues.apache.org/jira/browse/PARQUET-1866
> Project: Parquet
> Issue Type: Improvement
> Components: parquet-mr
> Affects Versions: 1.12.0
> Reporter: Xinli Shang
> Assignee: Xinli Shang
> Priority: Major
> Fix For: 1.12.0
>
>
> The parquet-mr repo has been using
> [ZSTD-JNI|https://github.com/luben/zstd-jni/tree/master/src/main/java/com/github/luben/zstd]
> for the parquet-cli project. It is a cleaner approach to use this JNI than
> using Hadoop ZSTD compression, because 1) on the developing box, installing
> Hadoop is cumbersome, 2) Older version of Hadoop doesn't support ZSTD.
> Upgrading Hadoop is another pain. This Jira is to replace Hadoop ZSTD with
> ZSTD-JNI for parquet-hadoop project.
> According to the author of ZSTD-JNI, Flink, Spark, Cassandra all use ZSTD-JNI
> for ZSTD.
> Another approach is to use https://github.com/airlift/aircompressor which is
> a pure Java implementation. But it seems the compression level is not
> adjustable in aircompressor.
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