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

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[@gurumoorthysivakolunthu9878]

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

[@soumikdas7709]

Nice explanation

[@sandeepnarwal8782]

Best Video on CZcams

[@williamhaque6183]

Wonderful. Cleared a lot of doubt.

[@andre__luiz__]

the best teacher!!!!!

[@nagabadsha]

Well explained, Thanks

[@gautam0086]

Very informative, thx

[@rajat_ComedyCorner]

Great job, Sir

[@srinubathina7191]

Wow super content
Thank You Sir

[@omkarm7865]

great explanation

[@jayaananthjayaram9228]

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

[@jsnode7696]

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 ?

[@jay_rana]

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

[@debojitpaul5779]

Where I acn find the whole video series?

[@balaji348]

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

[@nareshdulam58]

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

[@ScholarNest]

It is automatically refreshed

[@nareshdulam58]

Thank you @@ScholarNest .

[@Ramakrishna410]

How it is automatically refreshed..can you make an video on modified cache

[@Ramakrishna410]

It will bring only from memory after cache, but how spark onows if new data in source table when we are not reading the table..

[@karthikeyanr1171]

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