Briefly, this error occurs when Elasticsearch encounters a data frame transform task with incorrect parameters. This could be due to a configuration error or a mismatch between the expected and actual parameters. To resolve this issue, you can try the following: 1) Review the parameters of the data frame transform task and correct any errors. 2) If the task was created with an older version of Elasticsearch, it may be incompatible with the current version. Consider updating the task or reverting to the older version. 3) If the error persists, delete and recreate the task with the correct parameters.
This guide will help you check for common problems that cause the log ” Found data frame transform persistent task [” + id + “] with incorrect params ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: task, persistent, plugin.
Overview
A task is an Elasticsearch operation, which can be any request performed on an Elasticsearch cluster, such as a delete by query request, a search request and so on. Elasticsearch provides a dedicated Task API for the task management which includes various actions, from retrieving the status of current running tasks to canceling any long running task.
Examples
Get all currently running tasks on all nodes of the cluster
Apart from other information, the response of the below request contains task IDs of all the tasks which can be used to get detailed information about the particular task in question.
GET _tasks
Get detailed information of a particular task
Where clQFAL_VRrmnlRyPsu_p8A:1132678759 is the ID of the task in below request
GET _tasks/clQFAL_VRrmnlRyPsu_p8A:1132678759
Get all the current tasks running on particular nodes
GET _tasks?nodes=nodeId1,nodeId2
Cancel a task
Where clQFAL_VRrmnlRyPsu_p8A:1132678759 is the ID of the task in the below request
POST /_tasks/clQFAL_VRrmnlRyPsu_p8A:1132678759/_cancel?pretty
Notes
- The Task API will be most useful when you want to investigate the spike of resource utilization in the cluster or want to cancel an operation.
Overview
In Elasticsearch, persistent refers to cluster settings that persist across cluster restarts. This setting is used in Cluster Update API calls. Persistent settings can also be configured in the elasticsearch.yml file.
Examples
## enable shard routing
PUT /_cluster/settings
{
"persistent" : {
"cluster.routing.allocation.enable" : "all"
}
}
## enable rebalancing of shards
PUT /_cluster/settings
{
"persistent" : {
"cluster.routing.rebalance.enable" : "all"
}
}
## limit the heap size for fielddata
PUT /_cluster/settings
{
"persistent" : {
“indices.breaker.fielddata.limit”: "30%"
}
}Log Context
Log “Found data frame transform persistent task [” + id + “] with incorrect params” class name is TransportStartDataFrameTransformAction.java. We extracted the following from Elasticsearch source code for those seeking an in-depth context :
assert(existingTask.size() == 1);
PersistentTasksCustomMetaData.PersistentTask pTask = existingTask.iterator().next();
if (pTask.getParams() instanceof DataFrameTransform) {
return (PersistentTasksCustomMetaData.PersistentTask)pTask;
}
throw new ElasticsearchStatusException("Found data frame transform persistent task [" + id + "] with incorrect params";
RestStatus.INTERNAL_SERVER_ERROR);
}
} private void cancelDataFrameTask(String taskId; String dataFrameId; Exception exception; Consumer onFailure) {
