spark_read_json

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Read a JSON file into a Spark DataFrame

Read a JSON file into a Spark DataFrame

Usage
spark_read_json(sc, name, path, options = list(), repartition = 0, memory = TRUE, overwrite = TRUE)
Arguments
sc
The Spark connection
name
Name of table
path
The path to the file. Needs to be accessible from the cluster. Supports: "hdfs://" or "s3n://"
options
A list of strings with additional options.
repartition
Total of partitions used to distribute table or 0 (default) to avoid partitioning
memory
Load data eagerly into memory
overwrite
Overwrite the table with the given name if it already exists
Details

You can read data from HDFS (hdfs://), S3 (s3n://), as well as the local file system (file://).

If you are reading from a secure S3 bucket be sure that the AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY environment variables are both defined.

See Also

Other reading and writing data: spark_read_csv, spark_read_parquet, spark_write_csv, spark_write_json, spark_write_parquet

Aliases
  • spark_read_json
Documentation reproduced from package sparklyr, version 0.3.2, License: file LICENSE

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