diff --git a/connector/profiler/README.md b/connector/profiler/README.md index 9e0a58444c605..742b1a8bb5da3 100644 --- a/connector/profiler/README.md +++ b/connector/profiler/README.md @@ -16,7 +16,7 @@ or ## Executor Code Profiling -The spark profiler module enables code profiling of executors in cluster mode based on the [async profiler](https://github.com/async-profiler/async-profiler/blob/v3.0/README.md), a low overhead sampling profiler. This allows a Spark application to capture CPU and memory profiles for application running on a cluster which can later be analyzed for performance issues. The profiler captures [Java Flight Recorder (jfr)](https://access.redhat.com/documentation/es-es/red_hat_build_of_openjdk/17/html/using_jdk_flight_recorder_with_red_hat_build_of_openjdk/openjdk-flight-recorded-overview) files for each executor; these can be read by many tools including Java Mission Control and Intellij. +The spark profiler module enables code profiling of executors in cluster mode based on the [async profiler](https://github.com/async-profiler/async-profiler/blob/v4.0/README.md), a low overhead sampling profiler. This allows a Spark application to capture CPU and memory profiles for application running on a cluster which can later be analyzed for performance issues. The profiler captures [Java Flight Recorder (jfr)](https://access.redhat.com/documentation/es-es/red_hat_build_of_openjdk/17/html/using_jdk_flight_recorder_with_red_hat_build_of_openjdk/openjdk-flight-recorded-overview) files for each executor; these can be read by many tools including Java Mission Control and Intellij. The profiler writes the jfr files to the executor's working directory in the executor's local file system and the files can grow to be large, so it is advisable that the executor machines have adequate storage. The profiler can be configured to copy the jfr files to a hdfs location before the executor shuts down. @@ -95,7 +95,7 @@ Then enable the profiling in the configuration.