Briefly, this error occurs when an Elasticsearch job is triggered while a previous job with the same ID is still running. This can happen due to long-running jobs or overlapping schedules. To resolve this, you can increase the interval between job runs, ensure jobs are not scheduled too closely together, or optimize your Elasticsearch cluster to process jobs faster. Additionally, consider checking if the job is stuck and needs manual intervention to stop.
This guide will help you check for common problems that cause the log ” Schedule was triggered for job [” + getJobId() + “]; but prior indexer is still running ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: indexer, plugin, indexing.
Overview
Indexing is the process of adding documents to and updating documents on an Elasticsearch index.
Examples
In its simplest form, you can index a document like this:
POST /test/_doc { "message": "Opster Rocks Elasticsearch Management" }
This will create the index “test” (if it doesn’t already exist) and add a document with the source equal to the body of the POST call. In this case, the ID will be created automatically. If you repeat this command, a second document will be created with an identical source but a different ID.
Alternatively, you can do this:
PUT /test/_doc/1 { "message": "Opster Elasticsearch Management and Troubleshooting" }
This is almost the same, but in this case, the call sets the ID of the document to 1. If you repeat the command modifying the message, you will modify the original document, replacing the previous source with the latest source.
However note that this is NOT the same as an UPDATE operation, which is a different API and allows us to modify certain fields of the document while leaving others unchanged.
Notes and good things to know
You can set your own ID if necessary (especially if you later need to update the same ID) but this comes at a performance penalty. If you don’t need to update documents, then let Elasticsearch set its own ID automatically.
If you need to index many documents at once, it is much more efficient to use the BULK API to carry out these operations with a single call.
Indexing is not an immediate automatic process. Documents will not be available for search until the index has refreshed. Refresh time by default is 1 second. Increasing this time reduces the burden on the cluster of indexing, increasing indexing speed. It is possible to modify the refresh time in the index settings.
You can apply version control by setting the version parameter (?version=3) and indicating version_type=external. By doing this Elasticsearch will reject any index requests where the version specified is less than the current version. This can be useful when running distributed processes and you cannot guarantee that updated documents arrive in the correct order.
PUT test/_doc/1?version=20&version_type=external { "message" : "using external version the document will be modified only if version is greater than previous!" }
The process of indexing is as follows
The index request is sent to the primary shard. Once the primary shard is updated, then the replication process request will be relayed to the replica shards. The command will not return until the primary shard (at least) has been updated. For greater resilience, you can specify a minimum number of shard replicas to be available before proceeding with the operation by using the parameter ?wait_for_active_shards=2
You can also specify which specific shard the index operation is sent to by using the “routing” command. There are 2 reasons that this might be done:
- Certain Elasticsearch functions (parent-child documents) that require that the parent and child documents be held on the same shard.
- Secondly, it may be possible to increase search speeds and reduce load on Elasticsearch by storing similar documents together on the same shard and then specifying the routing for both indexing and searching. Although this can be done explicitly during indexing, it is not recommended. It would be preferable to set this up using the index mapping, so that the routing is determined by an ID value on the source document.
Log Context
Log “Schedule was triggered for job [” + getJobId() + “]; but prior indexer is still running ” classname is AsyncTwoPhaseIndexer.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :
final IndexerState currentState = state.get(); switch (currentState) { case INDEXING: case STOPPING: case ABORTING: logger.warn("Schedule was triggered for job [" + getJobId() + "]; but prior indexer is still running " + "(with state [" + currentState + "]"); return false; case STOPPED: logger.debug("Schedule was triggered for job [" + getJobId() + "] but job is stopped. Ignoring trigger.");
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