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go-stash is a high performance, free and open source server-side data processing pipeline that ingests data from Kafka, processes it, and then sends it to ElasticSearch.

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go-stash

go-stash is a high performance, free and open source server-side data processing pipeline that ingests data from Kafka, processes it, and then sends it to ElasticSearch.

go-stash is about 5x throughput more than logstash, and easy to deploy, only one executable file.

go-stash

Quick Start

Install

cd stash && go build stash.go

Quick Start

  • With binary
./stash -f etc/config.yaml
  • With docker, make sure the path of config file is correct.
docker run -d -v `pwd`/etc:/app/etc kevinwan/go-stash

The config.yaml example is as follows:

Clusters:
- Input:
    Kafka:
      Name: go-stash
      Log:
        Mode: file
      Brokers:
      - "172.16.48.41:9092"
      - "172.16.48.42:9092"
      - "172.16.48.43:9092"
      Topic: ngapplog
      Group: stash
      Conns: 3
      Consumers: 10
      Processors: 60
      MinBytes: 1048576
      MaxBytes: 10485760
      Offset: first
  Filters:
  - Action: drop
    Conditions:
      - Key: status
        Value: 503
        Type: contains
      - Key: type
        Value: "app"
        Type: match
        Op: and
  - Action: remove_field
    Fields:
    - message
    - source
    - beat
    - fields
    - input_type
    - offset
    - "@version"
    - _score
    - _type
    - clientip
    - http_host
    - request_time
  Output:
    ElasticSearch:
      Hosts:
      - "http://172.16.188.73:9200"
      - "http://172.16.188.74:9200"
      - "http://172.16.188.75:9200"
      Index: "go-stash-{{yyyy.MM.dd}}"
      MaxChunkBytes: 5242880
      GracePeriod: 10s
      Compress: false
      TimeZone: UTC

Details

input

Conns: 3
Consumers: 10
Processors: 60
MinBytes: 1048576
MaxBytes: 10485760
Offset: first

Conns

  • The number of links to kafka, the number of links is based on the number of cores of the CPU, usually <= the number of cores of the CPU.

Consumers

  • The number of open threads per connection, the calculation rule is Conns * Consumers, not recommended to exceed the total number of slices, for example, if the topic slice is 30, Conns * Consumers <= 30

Processors

  • The number of threads to process data, depending on the number of CPU cores, can be increased appropriately, the recommended configuration: Conns * Consumers * 2 or Conns * Consumers * 3, for example: 60 or 90

MinBytes MaxBytes

  • The default size of the data block from kafka is 1M~10M. If the network and IO are better, you can adjust it higher.

Offset

  • Optional last and first, the default is last, which means read data from kafka from the beginning

Filters

- Action: drop
  Conditions:
    - Key: k8s_container_name
      Value: "-rpc"
      Type: contains
    - Key: level
      Value: info
      Type: match
      Op: and
- Action: remove_field
  Fields:
    - message
    - _source
    - _type
    - _score
    - _id
    - "@version"
    - topic
    - index
    - beat
    - docker_container
    - offset
    - prospector
    - source
    - stream
- Action: transfer
  Field: message
  Target: data

- Action: drop

  • Delete flag: The data that meets this condition will be removed when processing and will not be entered into es
  • According to the delete condition, specify the value of the key field and Value, the Type field can be contains (contains) or match (match)
  • Splice condition Op: and, can also write or

- Action: remove_field

Remove_field_id: the field to be removed, just list it below

- Action: transfer

Transfer field identifier: for example, the message field can be redefined as a data field

Output

Index

  • Index name, indexname-{{yyyy.MM.dd}} for year. Month. Day, or {{yyyy-MM-dd}}, in your own format

MaxChunkBytes

  • The size of the bulk submitted to ES each time, default is 5M, can be adjusted according to the ES io situation.

GracePeriod

  • The default is 10s, which is used to process the remaining consumption and data within 10s after the program closes and exits gracefully

Compress

  • Data compression, compression will reduce the amount of data transferred, but will increase certain processing performance, optional value true/false, default is false

TimeZone

  • Default value is UTC, Universal Standard Time

ES performance write test

Test environment

  • stash server: 3 units 4 cores 8G
  • es server: 15 units 16 cores 64G

Key configuration

- Input:
      Conns: 3
      Consumers: 10
      Processors: 60
      MinBytes: 1048576
      MaxBytes: 10485760
  Filters:
  - Action: remove_field
    Fields:
    - Message
    - source
    - beat
    - fields
    - input_type
    - offset
    - request_time
  Output:
      Index: "nginx_pro-{{yyyy.MM.d}}"
      Compress: false
      MaxChunkBytes: 5242880
      TimeZone: UTC

Write speed is above 150k/s on average

go-stash

Acknowledgements

go-stash is powered by go-zero GitHub Repo stars GitHub forks for great performance!

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go-stash is a high performance, free and open source server-side data processing pipeline that ingests data from Kafka, processes it, and then sends it to ElasticSearch.

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