spark_read_json
From sparklyr v0.3.0
by Javier Luraschi
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
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