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Is there any business use-case where profile_metrics and drift_metrics are used by Databricks customers.If so,kindly provide the scenario where to leverage this feature e.g data lineage,table metadata updates.
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hey @pankaj2264. both profile metric and drift metric tables are created and used by Lakehouse monitoring to assess the performance of your model and data over time or relative to a baseline table. you can find all the relevant information here Intro...
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by
rocky5
• New Contributor III
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I wrote simple code:from pyspark.sql import SparkSession
from pyspark.sql.window import Window
from pyspark.sql.functions import row_number, max
import pyspark.sql.functions as F
streaming_data = spark.read.table("x")
window = Window.partitionBy("BK...
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Hi,In my opinion the result is correctWhat needs to be noted in the result is that it is sorted by the "Onboarding_External_LakehouseId" column so if there is "BK_AccountApplicationId" with the same code, it will be partitioned into 2 row_numbersJust...
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Hi!I receive three streams from a postgres CDC. These 3 tables, invoices users and products, need to be joined. I want to use a left join with respect the invoices stream. In order to compute correct results and release old states, I use watermarks a...
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Hi!I am exploring the read state functionality in spark streaming: https://docs.databricks.com/en/structured-streaming/read-state.htmlWhen I start a streaming query like this: (
...
.writeStream
.option("checkpointLocation", f"{CHECKPOIN...
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