I am trying to read avro messages from Kafka, using PySpark 2.4.0.
The spark-avro external module can provide this solution for reading avro files:
df = spark.read.format("avro").load("examples/src/main/resources/users.avro")
df.select("name", "favorite_color").write.format("avro").save("namesAndFavColors.avro")
However, I need to read streamed avro messages. The library documentation suggests using the from_avro() function, which is only available for Scala and Java.
Are there any other modules that support reading avro messages streamed from Kafka?
You would use kafka-avro-console-consumer which deserializes the binary avro data into json for you to read on the console. You can redirect > topic. txt to the console to read it. The connector name controls if a new consumer group is formed in distributed mode.
You can include spark-avro package, for example using --packages
(adjust versions to match spark installation):
bin/pyspark --packages org.apache.spark:spark-avro_2.11:2.4.0
and provide your own wrappers:
from pyspark.sql.column import Column, _to_java_column
def from_avro(col, jsonFormatSchema):
sc = SparkContext._active_spark_context
avro = sc._jvm.org.apache.spark.sql.avro
f = getattr(getattr(avro, "package$"), "MODULE$").from_avro
return Column(f(_to_java_column(col), jsonFormatSchema))
def to_avro(col):
sc = SparkContext._active_spark_context
avro = sc._jvm.org.apache.spark.sql.avro
f = getattr(getattr(avro, "package$"), "MODULE$").to_avro
return Column(f(_to_java_column(col)))
Example usage (adopted from the official test suite):
from pyspark.sql.functions import col, struct
avro_type_struct = """
{
"type": "record",
"name": "struct",
"fields": [
{"name": "col1", "type": "long"},
{"name": "col2", "type": "string"}
]
}"""
df = spark.range(10).select(struct(
col("id"),
col("id").cast("string").alias("id2")
).alias("struct"))
avro_struct_df = df.select(to_avro(col("struct")).alias("avro"))
avro_struct_df.show(3)
+----------+
| avro|
+----------+
|[00 02 30]|
|[02 02 31]|
|[04 02 32]|
+----------+
only showing top 3 rows
avro_struct_df.select(from_avro("avro", avro_type_struct)).show(3)
+------------------------------------------------+
|from_avro(avro, struct<col1:bigint,col2:string>)|
+------------------------------------------------+
| [0, 0]|
| [1, 1]|
| [2, 2]|
+------------------------------------------------+
only showing top 3 rows
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