pyspark.sql.DataFrameReader.json

DataFrameReader.json(path, schema=None, primitivesAsString=None, prefersDecimal=None, allowComments=None, allowUnquotedFieldNames=None, allowSingleQuotes=None, allowNumericLeadingZero=None, allowBackslashEscapingAnyCharacter=None, mode=None, columnNameOfCorruptRecord=None, dateFormat=None, timestampFormat=None, multiLine=None, allowUnquotedControlChars=None, lineSep=None, samplingRatio=None, dropFieldIfAllNull=None, encoding=None, locale=None, pathGlobFilter=None, recursiveFileLookup=None, allowNonNumericNumbers=None, modifiedBefore=None, modifiedAfter=None)[source]

Loads JSON files and returns the results as a DataFrame.

JSON Lines (newline-delimited JSON) is supported by default. For JSON (one record per file), set the multiLine parameter to true.

If the schema parameter is not specified, this function goes through the input once to determine the input schema.

New in version 1.4.0.

Parameters:
pathstr, list or RDD

string represents path to the JSON dataset, or a list of paths, or RDD of Strings storing JSON objects.

schemapyspark.sql.types.StructType or str, optional

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

primitivesAsStringstr or bool, optional

infers all primitive values as a string type. If None is set, it uses the default value, false.

prefersDecimalstr or bool, optional

infers all floating-point values as a decimal type. If the values do not fit in decimal, then it infers them as doubles. If None is set, it uses the default value, false.

allowCommentsstr or bool, optional

ignores Java/C++ style comment in JSON records. If None is set, it uses the default value, false.

allowUnquotedFieldNamesstr or bool, optional

allows unquoted JSON field names. If None is set, it uses the default value, false.

allowSingleQuotesstr or bool, optional

allows single quotes in addition to double quotes. If None is set, it uses the default value, true.

allowNumericLeadingZerostr or bool, optional

allows leading zeros in numbers (e.g. 00012). If None is set, it uses the default value, false.

allowBackslashEscapingAnyCharacterstr or bool, optional

allows accepting quoting of all character using backslash quoting mechanism. If None is set, it uses the default value, false.

modestr, optional
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. When inferring a schema, it implicitly adds a columnNameOfCorruptRecord field in an output schema.

  • DROPMALFORMED: ignores the whole corrupted records.

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

columnNameOfCorruptRecord: str, optional

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.

dateFormatstr, optional

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

timestampFormatstr, optional

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

multiLinestr or bool, optional

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

allowUnquotedControlCharsstr or bool, optional

allows JSON Strings to contain unquoted control characters (ASCII characters with value less than 32, including tab and line feed characters) or not.

encodingstr or bool, optional

allows to forcibly set one of standard basic or extended encoding for the JSON files. For example UTF-16BE, UTF-32LE. If None is set, the encoding of input JSON will be detected automatically when the multiLine option is set to true.

lineSepstr, optional

defines the line separator that should be used for parsing. If None is set, it covers all \r, \r\n and \n.

samplingRatiostr or float, optional

defines fraction of input JSON objects used for schema inferring. If None is set, it uses the default value, 1.0.

dropFieldIfAllNullstr or bool, optional

whether to ignore column of all null values or empty array/struct during schema inference. If None is set, it uses the default value, false.

localestr, optional

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.

pathGlobFilterstr or bool, optional

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. # noqa

recursiveFileLookupstr or bool, optional

recursively scan a directory for files. Using this option disables partition discovery. # noqa

allowNonNumericNumbersstr or bool

allows JSON parser to recognize set of “Not-a-Number” (NaN) tokens as legal floating number values. If None is set, it uses the default value, true.

  • +INF: for positive infinity, as well as alias of

    +Infinity and Infinity.

  • -INF: for negative infinity, alias -Infinity.

  • NaN: for other not-a-numbers, like result of division by zero.

modifiedBeforean optional timestamp to only include files with

modification times occurring before the specified time. The provided timestamp must be in the following format: YYYY-MM-DDTHH:mm:ss (e.g. 2020-06-01T13:00:00)

modifiedAfteran optional timestamp to only include files with

modification times occurring after the specified time. The provided timestamp must be in the following format: YYYY-MM-DDTHH:mm:ss (e.g. 2020-06-01T13:00:00)

Examples

>>>
>>> df1 = spark.read.json('python/test_support/sql/people.json')
>>> df1.dtypes
[('age', 'bigint'), ('name', 'string')]
>>> rdd = sc.textFile('python/test_support/sql/people.json')
>>> df2 = spark.read.json(rdd)
>>> df2.dtypes
[('age', 'bigint'), ('name', 'string')]
pyspark.sql.DataFrameReader.jdbc pyspark.sql.DataFrameReader.load