02-16-2023 11:03 AM
Hello,
i need to add a custom metadata into a avro file. The avro file containt data.
we have tried to use "option" within the write function but it's not taken without generated any error.
df.write.format("avro").option("avro.codec", "snappy").option("header", "metadata_key:metadata_value").mode("overwrite").save("/tmp/avro_with_metadata")
I'm seeking a solution to add a custom metadata into a data avro file.
Thanks,
Zakaria
02-23-2023 04:06 AM
Hi @zakaria belamri, You can add custom metadata to an Avro file in PySpark by creating an Avro schema with the custom metadata fields and passing it to the DataFrameWriter as an option. Here's an example code snippet that demonstrates how to do this:
from pyspark.sql import SparkSession
import pyspark.sql.functions as F
# create SparkSession
spark = SparkSession.builder.appName("AvroCustomMetadata").getOrCreate()
# create example DataFrame
df = spark.range(10).withColumn("value", F.lit("hello"))
# define custom metadata fields as a dictionary
custom_metadata = {
"key1": "value1",
"key2": "value2"
}
# create Avro schema with custom metadata fields
avro_schema = """
{
"type": "record",
"name": "ExampleRecord",
"fields": [
{"name": "id", "type": "long"},
{"name": "value", "type": "string"}
],
"metadata": {
"custom": %s
}
}
""" % (json.dumps(custom_metadata),)
# write DataFrame to Avro file with custom metadata
df.write.format("avro").option("avroSchema", avro_schema).save("example.avro")
# read Avro file and display custom metadata
read_df = spark.read.format("avro").load("example.avro")
print(read_df.schema.metadata["custom"])
Note that in this example, we use the JSON.dumps method to convert the dictionary of custom metadata to a JSON string that can be embedded in the Avro schema definition.
02-23-2023 04:06 AM
Hi @zakaria belamri, You can add custom metadata to an Avro file in PySpark by creating an Avro schema with the custom metadata fields and passing it to the DataFrameWriter as an option. Here's an example code snippet that demonstrates how to do this:
from pyspark.sql import SparkSession
import pyspark.sql.functions as F
# create SparkSession
spark = SparkSession.builder.appName("AvroCustomMetadata").getOrCreate()
# create example DataFrame
df = spark.range(10).withColumn("value", F.lit("hello"))
# define custom metadata fields as a dictionary
custom_metadata = {
"key1": "value1",
"key2": "value2"
}
# create Avro schema with custom metadata fields
avro_schema = """
{
"type": "record",
"name": "ExampleRecord",
"fields": [
{"name": "id", "type": "long"},
{"name": "value", "type": "string"}
],
"metadata": {
"custom": %s
}
}
""" % (json.dumps(custom_metadata),)
# write DataFrame to Avro file with custom metadata
df.write.format("avro").option("avroSchema", avro_schema).save("example.avro")
# read Avro file and display custom metadata
read_df = spark.read.format("avro").load("example.avro")
print(read_df.schema.metadata["custom"])
Note that in this example, we use the JSON.dumps method to convert the dictionary of custom metadata to a JSON string that can be embedded in the Avro schema definition.
02-24-2023 09:00 AM
Hi @zakaria belamri (Customer), Please don't forget to click on the "Select As Best" button whenever the information provided helps resolve your question.
02-24-2023 09:06 AM
Thank you. @zakaria belamri ! If you have any other questions or concerns, feel free to ask. Have a great day!
02-24-2023 09:08 AM
thank you a lot for your answer, it's very helpful.
I have a additionnal question please, is it possible to add a avro binnary metada inside the json avro_schema?
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