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Create a DataFrame with default column types

Spark/Big Dataeasy0.4 min readPremium
Frequency
Low
Asked at 1 company
Category
452
questions in Spark/Big Data
Difficulty Split
88E|81M|283H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
KPMG
Key Concepts Tested
pythonsparksql
Expert AnswerPremium
80 wordsIncludes code examplesInterview-ready
**Example**: ```python from pyspark.sql import SparkSession from pyspark.sql.types import StructType, StructField, StringType, IntegerType schema = StructType([ StructField("id", IntegerType()), StructField("name", StringType()), ]) df = spark.createDataFrame([], schema) # Or DDL: spark.createDataFrame([], "id int, name string") ``` **Why it matters**: Empty DataFrame with schema enables downstream operations without data; used for union, schema validation....
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