Data Caching in Apache Spark | Optimizing performance using Caching | When and when not to cache

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Very detailed... best ever explanation of a topic, Sir... This is amazing... Thank you, Sir....

gurumoorthysivakolunthu

I took your udemy course, its great. I have a doubt
I have a hive table, having parquet files with different schema(2 columns varying in data type)
when reading the data as dataframe, and writing it to another table, I am getting error:Parquet files cannot be converted
How to handle with schema data type mismatch ?

jsnode

can you post how to use iceberg in emr or using pyspark

jayaananthjayaram

where is the next part of the video, can you drop the link ?

jay_rana

Where I acn find the whole video series?

debojitpaul

Sir, please share writing spark streaming from Kafka topic and with consumer record and again sending that record to another topic

balaji

Are you going to answer rest of question on what happens to cache if table/view data modified?

nareshdulam

Although the content is good, Too lengthy video to explain this concept
This whole concept could be covered shortly

karthikeyanr

Data Caching in Apache Spark | Optimizing performance using Caching | When and when not to cache

Data Caching in Apache Spark | Optimizing performance using Caching | When and when not to cache

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