pyspark.sql.streaming.DataStreamReader.csv

DataStreamReader.csv(path, schema=None, sep=None, encoding=None, quote=None, escape=None, comment=None, header=None, inferSchema=None, ignoreLeadingWhiteSpace=None, ignoreTrailingWhiteSpace=None, nullValue=None, nanValue=None, positiveInf=None, negativeInf=None, dateFormat=None, timestampFormat=None, maxColumns=None, maxCharsPerColumn=None, maxMalformedLogPerPartition=None, mode=None, columnNameOfCorruptRecord=None, multiLine=None, charToEscapeQuoteEscaping=None, enforceSchema=None, emptyValue=None, locale=None, lineSep=None, pathGlobFilter=None, recursiveFileLookup=None)[source]

Loads a CSV file stream and returns the result as a DataFrame.

This function will go through the input once to determine the input schema if inferSchema is enabled. To avoid going through the entire data once, disable inferSchema option or specify the schema explicitly using schema.

Note

Evolving.

Parameters

  • path – string, or list of strings, for input path(s).

  • schema – an optional pyspark.sql.types.StructType for the input schema or a DDL-formatted string (For example col0 INT, col1 DOUBLE).

  • sep – sets a separator (one or more characters) for each field and value. If None is set, it uses the default value, ,.

  • encoding – decodes the CSV files by the given encoding type. If None is set, it uses the default value, UTF-8.

  • quote – sets a single character used for escaping quoted values where the separator can be part of the value. If None is set, it uses the default value, ". If you would like to turn off quotations, you need to set an empty string.

  • escape – sets a single character used for escaping quotes inside an already quoted value. If None is set, it uses the default value, \.

  • comment – sets a single character used for skipping lines beginning with this character. By default (None), it is disabled.

  • header – uses the first line as names of columns. If None is set, it uses the default value, false.

  • inferSchema – infers the input schema automatically from data. It requires one extra pass over the data. If None is set, it uses the default value, false.

  • enforceSchema – If it is set to true, the specified or inferred schema will be forcibly applied to datasource files, and headers in CSV files will be ignored. If the option is set to false, the schema will be validated against all headers in CSV files or the first header in RDD if the header option is set to true. Field names in the schema and column names in CSV headers are checked by their positions taking into account spark.sql.caseSensitive. If None is set, true is used by default. Though the default value is true, it is recommended to disable the enforceSchema option to avoid incorrect results.

  • ignoreLeadingWhiteSpace – a flag indicating whether or not leading whitespaces from values being read should be skipped. If None is set, it uses the default value, false.

  • ignoreTrailingWhiteSpace – a flag indicating whether or not trailing whitespaces from values being read should be skipped. If None is set, it uses the default value, false.

  • nullValue – sets the string representation of a null value. If None is set, it uses the default value, empty string. Since 2.0.1, this nullValue param applies to all supported types including the string type.

  • nanValue – sets the string representation of a non-number value. If None is set, it uses the default value, NaN.

  • positiveInf – sets the string representation of a positive infinity value. If None is set, it uses the default value, Inf.

  • negativeInf – sets the string representation of a negative infinity value. If None is set, it uses the default value, Inf.

  • dateFormat – sets the string that indicates a date format. Custom date formats follow the formats at `datetime pattern`_. This applies to date type. If None is set, it uses the default value, yyyy-MM-dd.

  • timestampFormat – sets the string that indicates a timestamp format. Custom date formats follow the formats at `datetime pattern`_. This applies to timestamp type. If None is set, it uses the default value, yyyy-MM-dd'T'HH:mm:ss[.SSS][XXX].

  • maxColumns – defines a hard limit of how many columns a record can have. If None is set, it uses the default value, 20480.

  • maxCharsPerColumn – defines the maximum number of characters allowed for any given value being read. If None is set, it uses the default value, -1 meaning unlimited length.

  • maxMalformedLogPerPartition – this parameter is no longer used since Spark 2.2.0. If specified, it is ignored.

  • mode –

    allows a mode for dealing with corrupt records during parsing. If None is

    set, it uses the default value, PERMISSIVE.

    • PERMISSIVE: when it meets a corrupted record, puts the malformed string into a field configured by columnNameOfCorruptRecord, and sets malformed fields to null. To keep corrupt records, an user can set a string type field named columnNameOfCorruptRecord in an user-defined schema. If a schema does not have the field, it drops corrupt records during parsing. A record with less/more tokens than schema is not a corrupted record to CSV. When it meets a record having fewer tokens than the length of the schema, sets null to extra fields. When the record has more tokens than the length of the schema, it drops extra tokens.

    • DROPMALFORMED: ignores the whole corrupted records.

    • FAILFAST: throws an exception when it meets corrupted records.

  • columnNameOfCorruptRecord – allows renaming the new field having malformed string created by PERMISSIVE mode. This overrides spark.sql.columnNameOfCorruptRecord. If None is set, it uses the value specified in spark.sql.columnNameOfCorruptRecord.

  • multiLine – parse one record, which may span multiple lines. If None is set, it uses the default value, false.

  • charToEscapeQuoteEscaping – sets a single character used for escaping the escape for the quote character. If None is set, the default value is escape character when escape and quote characters are different, \0 otherwise..

  • emptyValue – sets the string representation of an empty value. If None is set, it uses the default value, empty string.

  • locale – sets a locale as language tag in IETF BCP 47 format. If None is set, it uses the default value, en-US. For instance, locale is used while parsing dates and timestamps.

  • lineSep – defines the line separator that should be used for parsing. If None is set, it covers all \\r, \\r\\n and \\n. Maximum length is 1 character.

  • pathGlobFilter – an optional glob pattern to only include files with paths matching the pattern. The syntax follows org.apache.hadoop.fs.GlobFilter. It does not change the behavior of `partition discovery`_.

  • recursiveFileLookup – recursively scan a directory for files. Using this option disables `partition discovery`_.

>>> csv_sdf = spark.readStream.csv(tempfile.mkdtemp(), schema = sdf_schema)
>>> csv_sdf.isStreaming
True
>>> csv_sdf.schema == sdf_schema
True

New in version 2.0.

pyspark.sql.streaming.StreamingQueryManager pyspark.sql.streaming.DataStreamReader.format