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

helius_205 — Mon, 06 Apr 2026 03:39:12 GMT

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 ?

Re: Does a delta live table automatically perform increments without needing timestamp columns?

Sumit_7 — Mon, 06 Apr 2026 05:32:21 GMT

@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.

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

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

Re: Does a delta live table automatically perform increments without needing timestamp columns?