delta table datatype

Question

hello,

how is it possible to correct the column data types of delta table?

for example, when I create and populate the delta tables, the columns are of type string. now I would like to alter these column according to the type of data in columns, i.e. int, decimal, etc.

how can I do this?

notice that this is how I create the delta tables and populate at the same time.

df.write.format("delta").mode("overwrite").saveAsTable("db_name.tblname")

Answer 1

You may need to rewrite the table, so start by reading the existing table into a Spark datagrame, cast the columns to the desired data types and then write the df back to a new delta table with the desired schema (here is an example) :

import pyspark.sql.functions as F
df = spark.read.table("db_name.tblname")

df = df.withColumn("int_column", F.col("int_column").cast("int"))
df = df.withColumn("decimal_column", F.col("decimal_column").cast("decimal(10,2)"))

df.write.format("delta").mode("overwrite").saveAsTable("db_name.new_tblname")

Or, if you are familiar with Delta Lake column mapping, it can allow you to read and write data to a Delta table with a different schema than the table's actual schema :

# Enable column mapping for the table
spark.sql("ALTER TABLE db_name.tblname SET TBLPROPERTIES ('delta.columnMapping.enabled' = 'true')")

# Create a new Spark DataFrame with the desired schema
new_df = spark.createDataFrame([], ["int_column"])

# Write the DataFrame to the Delta table using the column mapping configuration
new_df.write.format("delta").mode("overwrite") \
    .option("delta.columnMapping.int_column", "string") \
    .saveAsTable("db_name.tblname")