spark_read_text

Read a Text file into a Spark DataFrame

Description

Read a text file into a Spark DataFrame.

Usage

spark_read_text(
  sc,
  name = NULL,
  path = name,
  repartition = 0,
  memory = TRUE,
  overwrite = TRUE,
  options = list(),
  whole = FALSE,
  ...
)

Arguments

Argument	Description
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? options | A list of strings with additional options. whole | Read the entire text file as a single entry? Defaults to FALSE. … | 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 https://docs.aws.amazon.com/sdk-for-java/v1/developer-guide/credentials.htmlWorking 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: https://hadoop.apache.org/docs/stable/hadoop-aws/tools/hadoop-aws/index.html#Authentication_propertiess3n authentication properties

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(), spark_save_table(), spark_write_avro(), 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()