Read CSV Stream
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.
If specified, the elements can be |
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_delta(),
stream_read_json(),
stream_read_kafka(),
stream_read_orc(),
stream_read_parquet(),
stream_read_socket(),
stream_read_text(),
stream_write_console(),
stream_write_csv(),
stream_write_delta(),
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)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.