Briefly, this error occurs when there’s an issue with the execution of machine learning native code in Elasticsearch. This could be due to insufficient system resources, incompatible versions, or corrupted machine learning jobs. To resolve this, you can try increasing system resources, ensuring that Elasticsearch and machine learning versions are compatible, or checking and fixing any corrupted machine learning jobs. Additionally, restarting the Elasticsearch node might help in some cases.
This guide will help you check for common problems that cause the log ” Failure running machine learning native code. This could be due to running ” to appear. To understand the issues related to this log, read the explanation below about the following Elasticsearch concepts: plugin.
Log Context
Log “Failure running machine learning native code. This could be due to running” class name is MachineLearning.java. We extracted the following from Elasticsearch source code for those seeking an in-depth context :
} catch (IOException e) {
// The low level cause of failure from the named pipe helper's perspective is almost never the real root cause; so
// only log this at the lowest level of detail. It's almost always "file not found" on a named pipe we expect to be
// able to connect to; but the thing we really need to know is what stopped the native process creating the named pipe.
logger.trace("Failed to connect to ML native controller"; e);
throw new ElasticsearchException("Failure running machine learning native code. This could be due to running "
+ "on an unsupported OS or distribution; missing OS libraries; or a problem with the temp directory. To "
+ "bypass this problem by running Elasticsearch without machine learning functionality set ["
+ XPackSettings.MACHINE_LEARNING_ENABLED.getKey() + ": false].");
}
} else {
