Document-Level Index Diff Between Two Elasticsearch Clusters

Document-Level Index Diff Between Two Elasticsearch Clusters #

INFINI Gateway is able to compare differences between two different indexes in the same or different clusters. In scenarios in which application dual writes, CCR, or other data replication solutions are used, differences can be periodically compared to ensure data consistency.

Function Demonstration #

How Is This Feature Configured? #

Setting a Target Cluster #

Modify the gateway.yml configuration file by setting two cluster resources source and target and adding the following configuration:

elasticsearch:
  - name: source
    enabled: true
    endpoint: http://localhost:9200
    basic_auth:
      username: test
      password: testtest
  - name: target
    enabled: true
    endpoint: http://localhost:9201
    basic_auth: #used to discovery full cluster nodes, or check elasticsearch's health and versions
      username: test
      password: testtest

Configuring a Contrast Task #

Add a service pipeline to handle the index document pulling and contrast of two clusters as follows:

pipeline:
  - name: index_diff_service
    auto_start: true
    keep_running: true
    processor:
    - dag:
        parallel:
          - dump_hash: #dump es1's doc
              indices: "medcl-test"
              scroll_time: "10m"
              elasticsearch: "source"
              output_queue: "source_docs"
              batch_size: 10000
              slice_size: 5
          - dump_hash: #dump es2's doc
              indices: "medcl-test"
              scroll_time: "10m"
              batch_size: 10000
              slice_size: 5
              elasticsearch: "target"
              output_queue: "target_docs"
        end:
          - index_diff:
              diff_queue: "diff_result"
              buffer_size: 1
              text_report: true #If data needs to be saved to Elasticsearch, disable the function and start the diff_result_ingest task of the pipeline.
              source_queue: 'source_docs'
              target_queue: 'target_docs'

In the above configuration, dump_hash is concurrently used to pull the medcl-a index of the source cluster and fetch the medcl-b index of the target cluster, and output results to terminals in text form.

Outputting Results to Elasticsearch #

If there are many difference results, you can save them to the Elasticsearch cluster, set the text_report parameter of the above index_diff processing unit to false, and add the following configuration:

pipeline:
  - name: diff_result_ingest
    auto_start: true
    keep_running: true
    processor:
      - json_indexing:
          index_name: "diff_result"
          elasticsearch: "source"
          input_queue: "diff_result"
          idle_timeout_in_seconds: 1
          worker_size: 1
          bulk_size_in_mb: 10 #in MB

Finally, import the dashboard to Kibana to achieve the following effect:

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