panbingkun commented on code in PR #46634:
URL: https://github.com/apache/spark/pull/46634#discussion_r1606341412
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common/utils/src/main/scala/org/apache/spark/internal/README.md:
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@@ -45,3 +45,29 @@ logger.error("Failed to abort the writer after failing to
write map output.", e)
## Exceptions
To ensure logs are compatible with Spark SQL and log analysis tools, avoid
`Exception.printStackTrace()`. Use `logError`, `logWarning`, and `logInfo`
methods from the `Logging` trait to log exceptions, maintaining structured and
parsable logs.
+
+## External third-party ecosystem access
+
+* If you want to output logs in `scala code` through the structured log
framework, you can define `custom LogKey` and use it in `scala` code as follows:
+
+```scala
+// External third-party ecosystem `custom LogKey` must be `extends LogKey`
+case object CUSTOM_LOG_KEY extends LogKey
+```
+```scala
+import org.apache.spark.internal.MDC;
+
+logInfo(log"${MDC(CUSTOM_LOG_KEY, "key")}")
+```
+
+* If you want to output logs in `java code` through the structured log
framework, you can define `custom LogKey` and use it in `java` code as follows:
+
+```java
+// External third-party ecosystem `custom LogKey` must be `implements LogKey`
+public static class CUSTOM_LOG_KEY implements LogKey { }
+```
+```java
+import org.apache.spark.internal.MDC;
+
+logger.error("Unable to delete key {} for cache", MDC.of(CUSTOM_LOG_KEY,
"key"));
+```
Review Comment:
If a third-party ecosystem wants to access a structured log framework,
should it customize one?
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