Serialize a Spark DataFrame into Apache Avro format


Serialize a Spark DataFrame into Apache Avro format. Notice this functionality requires the Spark connection sc to be instantiated with either an explicitly specified Spark version (i.e., spark_connect(..., version = <version>, packages = c("avro", <other package(s)>), ...)) or a specific version of Spark avro package to use (e.g., spark_connect(..., packages = c("org.apache.spark:spark-avro_2.12:3.0.0", <other package(s)>), ...)).


  avro_schema = NULL,
  record_name = "topLevelRecord",
  record_namespace = "",
  compression = "snappy",
  partition_by = NULL


Argument Description
x A Spark DataFrame or dplyr operation
path The path to the file. Needs to be accessible from the cluster. Supports the “hdfs://”, “s3a://” and “file://” protocols.
avro_schema Optional Avro schema in JSON format
record_name Optional top level record name in write result (default: “topLevelRecord”)
record_namespace Record namespace in write result (default: ““)
compression Compression codec to use (default: “snappy”)
partition_by A character vector. Partitions the output by the given columns on the file system.

See Also

Other Spark serialization routines: collect_from_rds(), spark_load_table(), spark_read_avro(), spark_read_binary(), spark_read_csv(), spark_read_delta(), spark_read_image(), spark_read_jdbc(), spark_read_json(), spark_read_libsvm(), spark_read_orc(), spark_read_parquet(), spark_read_source(), spark_read_table(), spark_read_text(), spark_read(), spark_save_table(), spark_write_csv(), spark_write_delta(), spark_write_jdbc(), spark_write_json(), spark_write_orc(), spark_write_parquet(), spark_write_source(), spark_write_table(), spark_write_text()