kafka-jira mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (KAFKA-6430) Improve Kafka GZip compression performance
Date Wed, 07 Feb 2018 00:46:00 GMT

    [ https://issues.apache.org/jira/browse/KAFKA-6430?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16354798#comment-16354798
] 

ASF GitHub Bot commented on KAFKA-6430:
---------------------------------------

ying-zheng opened a new pull request #4537: KAFKA-6430: Add buffer between Java data stream
and gzip stream
URL: https://github.com/apache/kafka/pull/4537
 
 
   *More detailed description of your change,
   if necessary. The PR title and PR message become
   the squashed commit message, so use a separate
   comment to ping reviewers.*
   
   *Summary of testing strategy (including rationale)
   for the feature or bug fix. Unit and/or integration
   tests are expected for any behaviour change and
   system tests should be considered for larger changes.*
   
   ### Committer Checklist (excluded from commit message)
   - [ ] Verify design and implementation 
   - [ ] Verify test coverage and CI build status
   - [ ] Verify documentation (including upgrade notes)
   

----------------------------------------------------------------
This is an automated message from the Apache Git Service.
To respond to the message, please log on GitHub and use the
URL above to go to the specific comment.
 
For queries about this service, please contact Infrastructure at:
users@infra.apache.org


> Improve Kafka GZip compression performance
> ------------------------------------------
>
>                 Key: KAFKA-6430
>                 URL: https://issues.apache.org/jira/browse/KAFKA-6430
>             Project: Kafka
>          Issue Type: Improvement
>          Components: clients, compression, core
>            Reporter: Ying Zheng
>            Priority: Minor
>
> To compress messages, Kafka uses DataOutputStream on top of GZIPOutputStream:
> 	new DataOutputStream(new GZIPOutputStream(buffer, bufferSize));
> To decompress messages, Kafka uses DataInputStream on top of GZIPInputStream:
>        new DataInputStream(new GZIPInputStream(buffer));
> This is very straight forward, but actually inefficient. For each message, in addition
to the key and value data, Kafka has to write about 30 some metadata bytes (slightly varies
in different Kafka version), including magic byte, checksum, timestamp, offset, key length,
value length etc. For each of these bytes, java DataOutputStream has to call write(byte) once.
Here is the awkward writeInt() method in DataOutputStream, which writes 4 bytes separately
in big-endian order. 
> {code}
>     public final void writeInt(int v) throws IOException {
>         out.write((v >>> 24) & 0xFF);
>         out.write((v >>> 16) & 0xFF);
>         out.write((v >>>  8) & 0xFF);
>         out.write((v >>>  0) & 0xFF);
>         incCount(4);
>     }
> {code}
> Unfortunately, GZIPOutputStream does not implement the write(byte) method. Instead, it
only provides a write(byte[], offset, len) method, which calls the corresponding JNI zlib
function. The write(byte) calls from DataOutputStream are translated into write(byte[], offset,
len) calls in a very inefficient way: (Oracle JDK 1.8 code)
> {code}
> class DeflaterOutputStream {
>     public void write(int b) throws IOException {
>         byte[] buf = new byte[1];
>         buf[0] = (byte)(b & 0xff);
>         write(buf, 0, 1);
>     }
>     public void write(byte[] b, int off, int len) throws IOException {
>         if (def.finished()) {
>             throw new IOException("write beyond end of stream");
>         }
>         if ((off | len | (off + len) | (b.length - (off + len))) < 0) {
>             throw new IndexOutOfBoundsException();
>         } else if (len == 0) {
>             return;
>         }
>         if (!def.finished()) {
>             def.setInput(b, off, len);
>             while (!def.needsInput()) {
>                 deflate();
>             }
>         }
>     }
> }
> class GZIPOutputStream extends DeflaterOutputStream {
>     public synchronized void write(byte[] buf, int off, int len)
>         throws IOException
>     {
>         super.write(buf, off, len);
>         crc.update(buf, off, len);
>     }
> }
> class Deflater {
> private native int deflateBytes(long addr, byte[] b, int off, int len, int flush);
> }
> class CRC32 {
>     public void update(byte[] b, int off, int len) {
>         if (b == null) {
>             throw new NullPointerException();
>         }
>         if (off < 0 || len < 0 || off > b.length - len) {
>             throw new ArrayIndexOutOfBoundsException();
>         }
>         crc = updateBytes(crc, b, off, len);
>     }
>     private native static int updateBytes(int crc, byte[] b, int off, int len);
> }
> {code}
> For each meta data byte, the code above has to allocate 1 single byte array, acquire
several locks, call two native JNI methods (Deflater.deflateBytes and CRC32.updateBytes).
In each Kafka message, there are about 30 some meta data bytes.
> The call stack of Deflater.deflateBytes():
> DeflaterOutputStream.public void write(int b) -> GZIPOutputStream.write(byte[] buf,
int off, int len) -> DeflaterOutputStream.write(byte[] b, int off, int len) -> DeflaterOutputStream.deflate()
-> Deflater.deflate(byte[] b, int off, int len) -> Deflater.deflate(byte[] b, int off,
int len, int flush) -> Deflater.deflateBytes(long addr, byte[] b, int off, int len, int
flush)
> The call stack of CRC32.updateBytes():
> DeflaterOutputStream.public void write(int b) -> GZIPOutputStream.write(byte[] buf,
int off, int len) -> CRC32.update(byte[] b, int off, int len) -> CRC32.updateBytes(int
crc, byte[] b, int off, int len)
> At Uber, we found that adding a small buffer between DataOutputStream and GZIPOutputStream
can speed up Kafka GZip compression speed by about 60% in average.
> {code}
>  -                    return new DataOutputStream(new GZIPOutputStream(buffer, bufferSize));
> +                    return new DataOutputStream(new BufferedOutputStream(new GZIPOutputStream(buffer,
bufferSize), 1 << 14));
> {code}
> The similar issue also exist in GZip decompression, which can be fixed by adding a buffer
with BufferedInputStream.
> We have tested this improvement on Kafka 10.2 / Oracle JDK 8, with the production traffic
at Uber:
> || Topic || Avg Message Size (bytes) || Vanilla Kafka Throughput (MB/s) || Kafka /w GZip
Buffer Throughput (MB/s) || Speed Up||
> | topic 1 | 197 | 10.9 | 21.9 | 2.0 |
> | topic 2 | 208 | 8.5 | 15.9 | 1.9 |
> | topic 3 | 624 | 15.3 | 20.2 | 1.3 |
> | topic 4 | 766 | 28.0 | 43.7 | 1.6 |
> | topic 5 | 1168 | 22.9 | 25.4 | 1.1 |
> | topic 6 | 165021 | 9.1 | 9.2 |  1.0 |



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)

Mime
View raw message