Read libsvm file into a Spark DataFrame.
spark_read_libsvm(sc, name, path, repartition = 0, memory = TRUE,
overwrite = TRUE, ...)
A spark_connection
.
The name to assign to the newly generated table.
The path to the file. Needs to be accessible from the cluster. Supports the "hdfs://", "s3a://" and "file://" protocols.
The number of partitions used to distribute the generated table. Use 0 (the default) to avoid partitioning.
Boolean; should the data be loaded eagerly into memory? (That is, should the table be cached?)
Boolean; overwrite the table with the given name if it already exists?
Optional arguments; currently unused.
Other Spark serialization routines: spark_load_table
,
spark_read_csv
,
spark_read_jdbc
,
spark_read_json
,
spark_read_parquet
,
spark_read_source
,
spark_read_table
,
spark_read_text
,
spark_save_table
,
spark_write_csv
,
spark_write_jdbc
,
spark_write_json
,
spark_write_parquet
,
spark_write_source
,
spark_write_table
,
spark_write_text