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Status

Current state: Under Discussion

Discussion thread: here [Change the link from the KIP proposal email archive to your own email thread]

JIRA: here [Change the link from KAFKA-1 to your own ticket]

Please keep the discussion on the mailing list rather than commenting on the wiki (wiki discussions get unwieldy fast).

Motivation

Compression is often used in Kafka to trade off extra CPU usage in Kafka clients for reduced storage and network resources on Kafka brokers. Compression is most commonly configured to be done by producers, though compression can also be configured to be performed by the brokers for situations where producers do not have spare CPU cycles. Regardless of the configuration used, the compression algorithm chosen will vary depending upon the needs of each use case.

To determine which compression algorithm to use, it is often helpful to be able to quantify the savings in storage, ingress bandwidth (if any), replication bandwidth, and egress bandwidth, all of which are a function of how much the compression algorithm reduces the overall size of the messages. Because the performance characteristics of each compression algorithm are highly dependent on the data being compressed, measuring the reduction in data size typically requires the user to produce data into Kafka using each compression algorithm and measure the resulting bandwidth utilization and log size for each use case. This process is time consuming and if the user is not careful, can easily provide vague or misleading results.

Public Interfaces

A new command line tool called kafka-compression-analyzer.sh that measures what the size of a log segment would be after compressing it using each of the compression types supported by Kafka. It is a read-only tool and does not modify the log segment being analyzed. This tool will will accept several command line parameters:

ParameterRequiredDescription
--logYesSpecifies the log file to analyze for the savings of compression.
--no-recompressionNoLeave compressed batches as-is, do not recompress using other compression types.

Output

The tool will print results to standard out. The tool reports information about the batches in the log segment (as more batching often helps improve the effectiveness of compression), the breakdown of compression types found in the log segment, and the results of applying each compression type. A sample output:

Sample Output 
Original log size: 536793767 bytes
Uncompressed log size: 536793767 bytes

Batch stats:
  16593/20220 batches contain >1 message
  Avg number of messages per batch: 3.68
  Avg batch size (original): 5180 bytes
  Avg batch size (uncompressed): 5180 bytes

Number of input batches by compression type:
  none: 20220

COMPRESSION-TYPE  COMPRESSED-SIZE  COMPRESSION-RATIO  SPACE-SAVINGS  AVG-RATIO/BATCH  TOTAL-TIME        SPEED
gzip                    118159324              4.543         22.01%            1.795     13875ms   36.90 MB/s
snappy                  160597012              3.342         29.92%            1.549      2678ms  191.16 MB/s 
zstd                    112737048              4.761         21.00%            1.775      5103ms  100.32 MB/s
lz4                     161711232              3.319         30.13%            1.576      2616ms  195.69 MB/s

Breakdown of outputs:

Compression Type - the configured compression type
Compressed Size - size in bytes of the log segment after compression
Compression Ratio - the ratio of the uncompressed size (or original size, if --no-recompression is set) to the compressed size
Space Savings - the reduction in size relative to the uncompressed size (or original size, if --no-recompression is set)
Avg Ratio/Batch - the mean compression ratio on a per-batch basis
Time - how long it took to compress all batches for the given compression type
Speed - the average rate at which the compression type is able to compress the log segment

Proposed Changes

kafka-compression-analyzer.sh aims to compress messages in the same manner a producer would and record the different in size of each batch. The tool sequentially iterates over each RecordBatch in a log file (very similar to kafka-dump-log.sh), compresses it into a new MemoryRecords object, and records the sizes of the batch both before and after compression. Since the tool only compresses existing batches as they were written to the log file and does not merge or split them, the tool effectively measures the resulting log size as if compression were enabled without other producer configurations being changed (ex. linger.ms).

If a RecordBatch is already compressed, by default the tool will decompress the batch and then recompress it using the other compression types. This allows the tool to report the resulting size of the log if all RecordBatches are compressed using each compression type. This can be disabled via the --no-recompression flag, in which case compression will only be done on uncompressed batches. Therefore, results with the --no-recompression flag will effectively show the impact of compression if all producers currently using compression.type=none were configured to use a given compression type.

Notes
  • The shell script will run kafka.tools.LogCompressionAnalyzer, which contains the source of the tool
  • There is precedent for read-only tools that operate on log files (i.e. kafka-dump-log.sh), if there are any consequences of running this tool on a log file the concerns would be shared
  • The tool does not spawn multiple threads
  • The tool will likely consume an entire core while running
    • Consider copying the log segment and running the tool on a non-broker machine to avoid starving the broker of CPU

Compatibility, Deprecation, and Migration Plan

This proposal adds a new tool and changes no existing functionality.

Rejected Alternatives

TODO

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