spark_read_text {sparklyr} | R Documentation

## Read a Text file into a Spark DataFrame

### Description

Read a text file into a Spark DataFrame.

### Usage

    spark_read_text(sc, name, path, repartition = 0, memory = TRUE,
      overwrite = TRUE, ...)

### Arguments

`sc` | A `spark_connection`.
`name` | The name to assign to the newly generated table.
`path` | The path to the file. Needs to be accessible from the cluster. Supports the "hdfs://", "s3a://" and "file://" protocols.
`repartition` | The number of partitions used to distribute the generated table. Use 0 (the default) to avoid partitioning.
`memory` | Boolean; should the data be loaded eagerly into memory? (That is, should the table be cached?)
`overwrite` | Boolean; overwrite the table with the given name if it already exists?
`...` | Optional arguments; currently unused.

### Details

You can read data from HDFS (`hdfs://`), S3 (`s3a://`), as well as the local file system (`file://`).

If you are reading from a secure S3 bucket be sure to set the following in your spark-defaults.conf `spark.hadoop.fs.s3a.access.key`, `spark.hadoop.fs.s3a.secret.key` or any of the methods outlined in the aws-sdk documentation Working with AWS credentials In order to work with the newer `s3a://` protocol also set the values for `spark.hadoop.fs.s3a.impl` and `spark.hadoop.fs.s3a.endpoint` . In addition, to support v4 of the S3 api be sure to pass the `-Dcom.amazonaws.services.s3.enableV4` driver options for the config key `spark.driver.extraJavaOptions` For instructions on how to configure `s3n://` check the hadoop documentation: s3n authentication properties

### See Also

Other Spark serialization routines: `spark_load_table`, `spark_read_csv`, `spark_read_jdbc`, `spark_read_json`, `spark_read_libsvm`, `spark_read_parquet`, `spark_read_source`, `spark_read_table`, `spark_save_table`, `spark_write_csv`, `spark_write_jdbc`, `spark_write_json`, `spark_write_parquet`, `spark_write_source`, `spark_write_table`, `spark_write_text`

[Package sparklyr version 0.8.4 Index]