stream_read_csv {sparklyr} | R Documentation |
Reads a CSV stream as a Spark dataframe stream.
stream_read_csv(sc, path, name = NULL, header = TRUE, columns = NULL, delimiter = ",", quote = "\"", escape = "\\", charset = "UTF-8", null_value = NULL, options = list(), ...)
sc |
A |
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 |
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 |
options |
A list of strings with additional options. |
... |
Optional arguments; currently unused. |
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
## 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) ## End(Not run)