spark_write_avro {sparklyr} | R Documentation |
Serialize a Spark DataFrame into Apache Avro format
Description
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 |
See Also
Other Spark serialization routines:
collect_from_rds()
,
spark_insert_table()
,
spark_load_table()
,
spark_read()
,
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_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()