spark_write_avro

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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)>), ...)).

Usage
spark_write_avro(
  x,
  path,
  avro_schema = NULL,
  record_name = "topLevelRecord",
  record_namespace = "",
  compression = "snappy",
  partition_by = NULL
)
Arguments
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: spark_load_table(), spark_read_avro(), spark_read_csv(), spark_read_delta(), 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()

Aliases
  • spark_write_avro
Documentation reproduced from package sparklyr, version 1.4.0, License: Apache License 2.0 | file LICENSE

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