Briefly, this error occurs when Elasticsearch takes more time to handle a request than the set warning threshold. This could be due to heavy indexing, slow queries, or insufficient resources. To resolve this, you can optimize your queries, increase your hardware resources, or adjust the warning threshold if it’s set too low. Also, consider using the Elasticsearch slow logs feature to identify slow queries and operations. Regular monitoring and maintenance of your Elasticsearch cluster can help prevent such issues.
This guide will help you check for common problems that cause the log ” handling request [{}][{}][{}][{}] took [{}ms] which is above the warn threshold of [{}ms] ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: threshold, request.
Overview
Elasticsearch uses several parameters to enable it to manage hard disk storage across the cluster.
What it’s used for
- Elasticsearch will actively try to relocate shards away from nodes which exceed the disk watermark high threshold.
- Elasticsearch will NOT locate new shards or relocate shards on to nodes which exceed the disk watermark low threshold.
- Elasticsearch will prevent all writes to an index which has any shard on a node that exceeds the disk.watermark.flood_stage threshold.
- The info update interval is the time it will take Elasticsearch to re-check the disk usage.
Examples
PUT _cluster/settings
{
"transient": {
"cluster.routing.allocation.disk.watermark.low": "85%",
"cluster.routing.allocation.disk.watermark.high": "90%",
"cluster.routing.allocation.disk.watermark.flood_stage": "95%",
"cluster.info.update.interval": "1m"
}
}Notes and good things to know
- You can use absolute values (100gb) or percentages (90%), but you cannot mix the two on the same cluster.
- In general, it is recommended to use percentages, since this will work in case the disks are resized.
- You can put the cluster settings on the elasticsearch.yml of each node, but it is recommended to use the PUT _cluster/settings API because it is easier to manage, and ensures that the settings are coherent across the cluster.
- Elasticsearch comes with sensible defaults for these settings, so think twice before modifying them. If you find you are spending a lot of time fine-tuning these settings, then it is probably time to invest in new disk space.
- In the event of the flood_stage threshold being exceeded, once you delete data, Elasticsearch should detect automatically that the block can be released (bearing in mind the update interval which could be, for instance, a minute). However if you want to accelerate this process, you can unblock an index manually, with the following call:
PUT /my_index/_settings
{
"index.blocks.read_only_allow_delete": null
}Common problems
Inappropriate cluster settings (if the disk watermark.low is too low) can make it impossible for Elasticsearch to allocate shards on the cluster. In particular, bear in mind that these parameters work in combination with other cluster settings (for example shard allocation awareness) which cause further restraints on how Elasticsearch can allocate shards.
Log Context
Log “handling request [{}][{}][{}][{}] took [{}ms] which is above the warn threshold of [{}ms]” classname is AbstractHttpServerTransport.java.
We extracted the following from Elasticsearch source code for those seeking an in-depth context :
handleIncomingRequest(httpRequest; httpChannel; httpRequest.getInboundException());
} finally {
final long took = threadPool.relativeTimeInMillis() - startTime;
final long logThreshold = slowLogThresholdMs;
if (logThreshold > 0 && took > logThreshold) {
logger.warn("handling request [{}][{}][{}][{}] took [{}ms] which is above the warn threshold of [{}ms]";
httpRequest.header(Task.X_OPAQUE_ID); httpRequest.method(); httpRequest.uri(); httpChannel; took; logThreshold);
}
}
}
