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Data Engineering
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Does a delta live table automatically perform increments without needing timestamp columns?

helius_205
New Contributor II

The code : 

import dlt
from pyspark.sql.functions import col

@dlt.table(
    name="silver_customers",
    comment="Cleaned customers data from bronze"
)
@dlt.expect("valid_email", "email IS NOT NULL")
@dlt.expect("valid_customer_id", "customer_id IS NOT NULL")
def silver_customers():
    return (
        spark.read.table("bronze.demo.customers")
        .dropDuplicates(["customer_id"])
        .select(
            "customer_id",
            "name",
            "email"
        )
    ) and the UI i have  
 
 

this table run incrementally?

Can some one confirm this  ?

 
 

 

 

1 ACCEPTED SOLUTION

Accepted Solutions

Sumit_7
Honored Contributor II

@helius_205 I doubt, do check the execution mode ~ should be triggered. Also it's a normal read instead of readStream. Read Docs for better understanding.

View solution in original post

1 REPLY 1

Sumit_7
Honored Contributor II

@helius_205 I doubt, do check the execution mode ~ should be triggered. Also it's a normal read instead of readStream. Read Docs for better understanding.