Data is not loaded when creating two different streaming table from one delta live table pipeline

[zero234]

 i am trying to create 2 streaming tables in one DLT pipleine , both read json data from different locations and both have different schema , the pipeline executes but no data is inserted in both the tables.
where as when i try to run each table individually they execute perfectly

is it because DLT cannot process two different streaming table at once.?

DF = spark.readStream.format("json") \

      .schema(schema) \

      .option("header", True) \

      .option("nullValue", "") \

      .load(source_path + "/*.json")

[Mounika_Tarigop]

Delta Live Tables (DLT) can indeed process multiple streaming tables within a single pipeline.

Here are a few things to check:

1) Verify that each streaming table has a unique checkpoint location. Checkpointing is crucial for maintaining the state of streaming queries, and conflicts can arise if the same location is used for multiple streams.

2) Ensure that first_schema and second_schema are defined correctly and match the structure of the JSON data in first_source_path and second_source_path, respectively.