No handler for udf/udaf/udtf for function

[databicky]

i created one function using jar file which is present in the cluster location, but when executing the hive query it is showing error as no handler for udf/udaf/udtf . this queries is running fine in hd insight clusters but when running in databricks it is showing error.

 

[Kaniz]

Hi @databicky , 

The error message "No handler for UDF/UDAF/UDTF" typically occurs when Spark cannot locate the UDF/UDAF/UDTF you registered. This can happen if the JAR file containing the UDF/UDAF/UDTF is not correctly loaded into Spark or the function signature is not precisely defined.

To resolve this issue, you can try the following steps:

1. Check that the jar file containing the UDF/UDAF/UDTF is correctly loaded into Spark. One way to do this is by checking that the jar file is listed in the output of the following command:

spark.conf.get("spark.jars")

If the jar file is not listed, you can add it to Spark using the following command:

spark.conf.set("spark.jars", "/path/to/your/jar/file.jar")

Replace /path/to/your/jar/file.jar with the actual path to the jar file.

2. Verify that the function signature is correctly defined. The function's signature determines the number and types of input arguments and the return type. If the signature is not correctly defined, Spark may be unable to locate and execute the function.

   You can verify the function signature using the following command

spark.catalog.listFunctions()

This will list all the functions registered with Spark. Verify that the function name, input arguments, and return type are correctly defined.

3. Ensure you correctly call the UDF/UDAF/UDTF in your Spark SQL query. The function name and input arguments must match the registered UDF/UDAF/UDTF.

   For example, to call a UDF named my_udf taking one integer argument, you would use it in a query like this

from pyspark.sql.functions import udf

   my_udf = udf(lambda x: x * 2, IntegerType())

   spark.udf.register("my_udf", my_udf)

   spark.sql("SELECT my_udf(id) as doubled_id FROM my_table")

In this example, my_udf takes one input argument id and returns doubled_id. When called, my_udf multiplies the input argument id by 2.

4. If the above steps do not resolve the issue, try running your query without the UDF/UDAF/UDTF to ensure the query itself is correct. You can also try restarting your Spark cluster to see if this resolves the issue

[databicky]

Thanks kaniz, is there any chance to view that jar file code? i tried dbutils.fs.head but the output is not in proper format. that jar file is the existing one. could you please help me on tht

[Kaniz · Accepted solution]

Hi @databicky ,

You can use the jar tf command to list the files inside a JAR file and then use dbutils.fs.head to view the contents of the individual files.

HereYou can extract the contents of a JAR file in Databricks by using the jar xf <jar-file> command in a %sh shell command in a notebook cell. This command extracts the contents of the JAR file into the current directory.

Here's an example code snippet:

%sh
jar xf jspark.jar
ls -R

This command extracts all of the files from the "jspark.jar" file into the current directory. The ls -R command lists all of the files in the current directory recursively, which allows you to see the extracted files.

If you want to view or modify the Java code inside the JAR file, you can decompile the code using a Java decompiler program such as JD-GUI or Fernflower. These programs can decompile the .class files inside the JAR file into Java code that you can view, modify, or recompile.

Here's an example code snippet for decompiling a JAR file using JD-GUI:

%sh
# Download the JD-GUI Java decompiler
wget https://github.com/java-decompiler/jd-gui/releases/download/v1.6.6/jd-gui-1.6.6.jar -O jd-gui.jar

# Run JD-GUI and open the JAR file
java -jar jd-gui.jar jspark.jar

This command downloads the JD-GUI decompiler program and then runs it to open the JAR file. You can use the JD-GUI program to view the decompiled Java code within the JAR file.

[databicky]

@Kaniz this post i can't edit

[databicky]

@Kaniz  how to edit this post?