schema (DataStreamReader)

Specifies the input schema. Some data sources (for example, JSON) can infer the input schema automatically from data. Specifying the schema here allows the data source to skip schema inference and speed up data loading.

Syntax

schema(schema)

Parameters

Parameter	Type	Description
schema	StructType or str	A StructType object or a DDL-formatted string (for example, col0 INT, col1 DOUBLE).

Returns

DataStreamReader

Examples

Python

from pyspark.sql.types import StructField, StructType, StringType
spark.readStream.schema(StructType([StructField("data", StringType(), True)]))
# <...streaming.readwriter.DataStreamReader object ...>
spark.readStream.schema("col0 INT, col1 DOUBLE")
# <...streaming.readwriter.DataStreamReader object ...>

Specify a different schema for a CSV file:

Python

import tempfile
with tempfile.TemporaryDirectory(prefix="schema") as d:
    spark.readStream.schema("col0 INT, col1 STRING").format("csv").load(d).printSchema()
    # root
    #  |-- col0: integer (nullable = true)
    #  |-- col1: string (nullable = true)