stream_read_csv
Read CSV Stream
Reads a CSV stream as a Spark dataframe stream.
Usage
stream_read_csv(sc, path, name = NULL, header = TRUE, columns = NULL,
delimiter = ",", quote = "\"", escape = "\\",
charset = "UTF-8", null_value = NULL, options = list(), ...)Arguments
- sc
A
spark_connection.- path
The path to the file. Needs to be accessible from the cluster. Supports the "hdfs://", "s3a://" and "file://" protocols.
- name
The name to assign to the newly generated stream.
- header
Boolean; should the first row of data be used as a header? Defaults to
TRUE.- columns
A vector of column names or a named vector of column types.
- delimiter
The character used to delimit each column. Defaults to ','.
- quote
The character used as a quote. Defaults to '"'.
- escape
The character used to escape other characters. Defaults to '\'.
- charset
The character set. Defaults to "UTF-8".
- null_value
The character to use for null, or missing, values. Defaults to
NULL.- options
A list of strings with additional options.
- ...
Optional arguments; currently unused.
See Also
Other Spark stream serialization: stream_read_json,
stream_read_kafka,
stream_read_orc,
stream_read_parquet,
stream_read_scoket,
stream_read_text,
stream_write_console,
stream_write_csv,
stream_write_json,
stream_write_kafka,
stream_write_memory,
stream_write_orc,
stream_write_parquet,
stream_write_text
Examples
# NOT RUN {
sc <- spark_connect(master = "local")
dir.create("csv-in")
write.csv(iris, "csv-in/data.csv", row.names = FALSE)
csv_path <- file.path("file://", getwd(), "csv-in")
stream <- stream_read_csv(sc, csv_path) %>% stream_write_csv("csv-out")
stream_stop(stream)
# }
# NOT RUN {
# }