topic Re: Failed to merge incompatible data types LongType and StringType in Data Engineering

Failed to merge incompatible data types LongType and StringType

tassiodahora — Mon, 23 May 2022 13:00:35 GMT

Guys, good morning!

I am writing the results of a json in a delta table, only the json structure is not always the same, if the field does not list in the json it generates type incompatibility when I append

(dfbrzagend.write

.format("delta")

.mode("append")

.option("inferSchema", "true")

.option("path",brzpath)

.option("schema",defaultschema)

.saveAsTable(brzbdtable))

Failed to merge fields 'age_responsavelnotafiscalpallet' and 'age_responsavelnotafiscalpallet'. Failed to merge incompatible data types LongType and StringType

Re: Failed to merge incompatible data types LongType and StringType

Anonymous — Mon, 06 Jun 2022 12:39:36 GMT

Hi @Tássio Santos

The delta table performs schema validation of every column, and the source dataframe column data types must match the column data types in the target table. If they don’t match, an exception is raised.

For reference-

https://docs.databricks.com/delta/delta-batch.html#schema-validation-1

you can cast the column explicitly before writing it to target table to avoid this

Re: Failed to merge incompatible data types LongType and StringType

ifun — Fri, 25 Nov 2022 10:06:00 GMT

The following example shows changing a column type:

(spark.read.table(...)
  .withColumn("birthDate", col("birthDate").cast("date"))
  .write
  .mode("overwrite")
  .option("overwriteSchema", "true")
  .saveAsTable(...)
)

Details see https://docs.databricks.com/delta/update-schema.html