How do you access a streaming live table's snapshots?

[logan0015]

I have read that delta live tables will keep a history of 7 days. However after creating a streaming live table and using the dlt.apply_changes function. With this code

def run_pipeline(table_name,keys,sequence_by):
    lower_table_name = table_name.lower()
    @dlt.view(name = f"{lower_table_name}_schema",
                     comment= "Test")
    def create_raw_schema():
        return(spark.read.format("parquet")
              .option("inferschema", True)
              .load(f"s3://mybucket/test/dbo/{table_name}/")
              .limit(10)
              )
 
    #creating hist table
    @dlt.table(name=f"s{lower_table_name}_hist",
                   comment = "test")
    def create_hist_table():
      return (
        spark.readStream.format("cloudFiles")
          .option("cloudFiles.format", "parquet")
          .schema(dlt.read(f"{lower_table_name}_schema").schema)
          .load(f"s3://mybucket/test/dbo/{table_name}/")
      )
 
    #creating current table
    dlt.create_streaming_live_table(
        name = f"{lower_table_name}",
        path = f"s3://mybucket/test/cdc/{table_name}__ct/")
    
    dlt.apply_changes(
        target = f"{lower_table_name}",
        source = f"{lower_table_name}_hist",
        keys = keys,
        sequence_by = col(sequence_by)
    )

when I attempt to access any version history using

SELECT * FROM dlt.my_table TIMESTAMP AS OF "2022-10-10"

I get this message "Cannot time travel views."

[Hubert-Dudek]

Which tables from your example do you want to query, as none of them is my_table?

[logan0015]

I've changed some of code to remove any personal information. The table name is being passed into the pipeline's function from another section of code. my_table was just an example name.

[Anonymous]

Hi @Logan Nicol​ 

Hope all is well! Just wanted to check in if you were able to resolve your issue and would you be happy to share the solution or mark an answer as best? Else please let us know if you need more help. 

We'd love to hear from you.

Thanks!