Last active
November 24, 2018 08:36
-
-
Save RajaShyam/1c3ae289b5cb00160081e0008677d1c2 to your computer and use it in GitHub Desktop.
Spark Streaming
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Dropwizard metrics: | |
================== | |
1. Push metrics into Ganglia, Graphite etc..(Can be enabed using SQL configuration) | |
spark.conf.set("spark.sql.streaming.metricsEnabled","true") | |
2. Enable INFO or DEBUG logging levels for org.apache.spark.sql.kafka010.KafkaSource to see what happens inside. | |
Add the following line to conf/log4j.properties: | |
log4j.logger.org.apache.spark.sql.kafka010.KafkaSource=DEBUG | |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Techniques: | |
========== | |
Source: https://databricks.com/session/apache-spark-streaming-programming-techniques-you-should-know | |
- Self contained stream generation | |
- Refreshing external data | |
- Structured streaming capability | |
- keeping arbitary state | |
- Probabilistic accumulators | |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment