Before you begin reading this guide, we recommend you run Elasticsearch Error Check-Up which can resolve issues that cause many errors.
This guide will help you check for common problems that cause the log ” Failed to execute pipeline for a bulk request ” to appear. It’s important to understand the issues related to the log, so to get started, read the general overview on common issues and tips related to the Elasticsearch concepts: bulk and request.
Advanced users might want to skip right to the common problems section in each concept or try running the Check-Up which analyses ES to pinpoint the cause of many errors and provides suitable actionable recommendations how to resolve them (free tool that requires no installation).
Overview
In Elasticsearch, when using the Bulk API it is possible to perform many write operations in a single API call, which increases the indexing speed. Using the Bulk API is more efficient than sending multiple separate requests. This can be done for the following four actions:
Examples
The bulk request below will index a document, delete another document, and update an existing document.
POST _bulk
{ "index" : { "_index" : "myindex", "_id" : "1" } }
{ "field1" : "value" }
{ "delete" : { "_index" : “myindex", "_id" : "2" } }
{ "update" : {"_id" : "1", "_index" : "myindex"} }
{ "doc" : {"field2" : "value5"} }Notes
- Bulk API is useful when you need to index data streams that can be queued up and indexed in batches of hundreds or thousands, such as logs.
- There is no correct number of actions or limits to perform on a single bulk call, but you will need to figure out the optimum number by experimentation, given the cluster size, number of nodes, hardware specs etc.
Log Context
Log “Failed to execute pipeline for a bulk request” classname is TransportBulkAction.java
We extracted the following from Elasticsearch source code for those seeking an in-depth context :
logger.debug(() -> new ParameterizedMessage("failed to execute pipeline [{}] for document [{}/{}/{}]";
indexRequest.getPipeline(); indexRequest.index(); indexRequest.type(); indexRequest.id()); exception);
bulkRequestModifier.markCurrentItemAsFailed(exception);
}; (exception) -> {
if (exception != null) {
logger.error("failed to execute pipeline for a bulk request"; exception);
listener.onFailure(exception);
} else {
long ingestTookInMillis = TimeUnit.NANOSECONDS.toMillis(System.nanoTime() - ingestStartTimeInNanos);
BulkRequest bulkRequest = bulkRequestModifier.getBulkRequest();
ActionListener actionListener = bulkRequestModifier.wrapActionListenerIfNeeded(ingestTookInMillis;
Run the Check-Up to get customized recommendations like this:
Run Check-Up
The high disk watermark threshold is about to be reached in specific nodes
Description
There are various “watermark” thresholds on each Elasticsearch cluster. When the high disk watermark threshold has been exceeded, it means disk space is running out. The node will…
Recommendations
Based on your specific ES deployment you should…
X-PUT curl -H [a customized code snippet to resolve the issue]