Spark error code 13

Spark is an open-source processing system used for big data workloads. By using Spark, you can get access to different applications such as SQL, machine learning, graph computation, and system processing, all in one location. Some of the key features of Spark that make it preferable are, Lighting fast processing speed, easy to use, supports sophisticated analytics, real-time stream processing, and flexibility. The chance for an error in Spark is less. Even if an error occurs, you can resolve it easily. The Spark error code 13 is the common one encountered by most of the users.

This error usually occurs when you try to run a program on a cluster using YARN.

Step 1:As per the experts, the Spark error code 13 occurs when the SparkContext doesn’t initialize in time.

Step 2:If you encounter this error, check your Yarn application log to know the detailed information about this error.

Step 3:Check if you have written a plain python script without creating SparkContext/SparkSession. If yes, perform the necessary steps to create SparkContext.

Step 4:Check if the Spark JARS are causing the issue.

Step 5:If yes, move all the Spark JARS data in the spark-archive.zip folder.

Step 6:Now, move the spark-archive.zip folder in the HDFS location.

Step 7:If you encounter the Spark error code 13 while using Polynote in the YARN-cluster mode, then test YARN-client mode inside Docker and see the results.

Step 8:Check if the error code is resolved.

Step 9:If not, check the internal IP address of the running container.

Step 10:If the running container's internet IP address is 172.17.0.2, you can connect the Spark Driver to Polynote because Polynote is not compatible with the 172.17.0.2 IP address.

Step 11:Try another IP address to connect the Spark Driver to Polynote.

If the Spark error code 13 persists, contact us.