Problem:
Need Explanation for the Pipeline: Our client has encountered a scenario in their Elasticsearch setup that requires clarification and understanding. The specific concern revolves around the configuration of the Logstash pipeline, more precisely, the interaction between the defined schedule and query parameters.
Logstash Configuration
LogstashConfig:
pipelines.yml: |
- pipeline.id: logstash-output-broker
schedule: "*/5 * * * *"
query: '{
"query": {
"bool": {
"filter": {
"range": {
"@timestamp": {
"format": "strict_date_optional_time",
"gte": "now-10m",
"lte": "now"
}
}
}
}
}
}'
Process:
Step 1: Schedule vs. Query
Schedule: The schedule is defined to run the Logstash pipeline every 5 minutes, as indicated by the cron-like expression “*/5 * * * *.” Query: The query retrieves data for the last 10 minutes, resulting in overlapping queries.
Step 2: Purpose of the Query
The purpose of the query is to continuously retrieve slices of data for the specified time range, ensuring that the Logstash pipeline stays updated with recent data and is in sync with the Elasticsearch index.
Step 3: Scrolling Mechanism
The configuration includes scroll => "2m," which means that if the query results exceed the default 10,000 records, Logstash will fetch the data in slices every 2 minutes. This mechanism is crucial for handling large datasets efficiently.
Solution:
The solution addresses the interaction between the schedule and query parameters in the Logstash pipeline configuration. The schedule runs the pipeline every 5 minutes, while the query retrieves data for the last 10 minutes, resulting in overlapping queries. The query continuously fetches recent data slices to keep the pipeline updated and synchronized with the Elasticsearch index. Additionally, the scrolling mechanism, specified as scroll => "2m,", efficiently handles large datasets by fetching data in slices every 2 minutes, especially when query results exceed the default limit of 10,000 records.
Conclusion:
Upon analysis, it is evident that the query is designed to retrieve data for the last 10 minutes every 5 minutes, ensuring a continuous and timely update of the Logstash pipeline. Although the query may not yield immediate results, it serves the purpose of fetching slices of data for storage, retrieval, or plotting. This configuration aligns with common practices for maintaining an up-to-date Logstash pipeline in Elasticsearch setups.