121. Databricks | Pyspark| AutoLoader: Incremental Data Load

Azure Databricks Learning: Databricks and Pyspark: AutoLoader: Incremental Data Load
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AutoLoader in Databricks is a crucial feature that streamlines the process of ingesting and processing large volumes of data efficiently. This automated data loading mechanism is instrumental for real-time or near-real-time data pipelines, allowing organizations to keep their data lakes up-to-date with minimal manual intervention. By automatically detecting and loading new or modified files from cloud storage, AutoLoader enhances data engineers' productivity, reduces latency in data availability, and ensures data accuracy. It plays a pivotal role in enabling timely insights and analytics, making it an indispensable component in modern data architectures.
To get more understanding, watch this video
• 121. Databricks | Pysp...
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[@sravankumar1767]

SUPERB EXPLANATION Raja 👌 👏 👍 came with New Topic

[@rajasdataengineering7585]

Thanks Sravan👍

[@sowjanyagvs7780]

very detailed explanation, am a newbiee to databricks but with your explanations i feel that i am pro now :) thanks a lot raja

[@rajasdataengineering7585]

Glad to hear that! Keep watching

[@thepakcolapcar]

nicely explained. Thanks

[@rajasdataengineering7585]

Glad it was helpful!

[@sumitchandwani9970]

Most awaited topic

[@rajasdataengineering7585]

Hope it provides insight about autoloader

[@sumitchandwani9970]

Thanks for the amazing video I'm trying to load 4 years worth of historical data with around a 1 million files per day I tried to use autoloader and it's taking 1 day to load just 22 hours worth of data Using directory listing method Can you give me some recommendations to load this data as fast as possible

[@nithishreddy725]

@@sumitchandwani9970 Hi Sumit , Did you figure out answer for this?

[@sumitchandwani9970]

@@nithishreddy725 yes I used file notification mode and added options to backfill File notification is 10x faster then directory listing so it took around a month to load and catch-up to the lastest data but it worked

[@3a8saisamireddi61]

superb👌content!

[@rajasdataengineering7585]

Thanks ✌️

[@HarshitSingh-lq9yp]

Where can we get the demo notebook that you have shown in the lecture, would appreciate the response, thanks!

[@trilokinathji31]

34:44 why trigger while writing? Please make video what are available option in trigger.

[@anjumanrahman1468]

Thanks Raja for the entire Databricks Playlist. Could you please make tutorial videos on Unity catalog

[@rajasdataengineering7585]

Sure Anjuman, will create a video for unity catalogue

[@ranjansrivastava9256]

Dear Raja, if possible can you please create a live demo on this Auto Loader topics. It's very informative and important for the project point of view.

[@thepakcolapcar]

sorry, one more question related to autoloader. In case if a databricks notebook is moved converted to be run on EMR cluster, does the autoloader equivalent compatible feature exists on EMR side? Asking because I believe autoloader is databricks specific feature

[@rajasdataengineering7585]

Yes that's right. Autoloader is specific to databricks, not spark. So EMR cluster can't support auto loader

[@thepakcolapcar]

Thank you@@rajasdataengineering7585

[@hemantkmr62]

thanks for the detailed video. small question how you got the queue_sas?

[@jhonsen9842]

Exellent. I have one question. Most of the time Interviewer ask on SchemaEvolution what is the ideal option to tell among those four you mentioned or its depend on type of data and type of processing you do.

[@pavankumarveesam8412]

So raj over here maxfileage is used to get the latest files or two perform incremental load is it?, as i cannot see any code in the video wth incremental load operation like water mark metho in adf

[@lucaslira5]

Is it possible to use 1 auto loader notebook for several tables changing the path dynamically coming from the data factory?

[@rajasdataengineering7585]

Yes that is possible

[@lucaslira5]

can you make a video using data factory + auto loader?@@rajasdataengineering7585

[@meghaparmar7510]

can you please add link to download the notebook that you used to explain

[@prabhatgupta6415]

Hello Sir. i am very much confused. I want to know how people used to apply incremental load in azure DE when autoloader was not there. Please create a video on that. Untill and unless we know about the old method we cant understand the solved Problem. How company used to follow upsert in azure de when data used to keep on changing.?

[@rajasdataengineering7585]

Hi Prabhat, DE projects used to follow bunch of old methods and I have covered few of them in this video before getting into auto loader. One of the common approach was water mark method

[@prabhatgupta6415]

Hello again i have same question i understood using watermark we loaded new data to landing...how can feed the new files to bronze, shall we read whole folder through spark read api. suppose cust1.csv came on first day and cust2.csv came on second day...same goes on for third file as well. so how people used to read the latest file here...we cant directly read third day file bcoz we need to make it dynamic to read latest file so that it could feed it to bronze.Please do answer here@@rajasdataengineering7585

[@hritiksharma7154]

Hi Raja, I am getting an error in azure databricks interactive cluster as driver is up but unresponsive likely due to GC. Any idea how to solve this issue ? Can we increase heap memory for this issue ?

[@rajasdataengineering7585]

Hi Hritik, yes you can increase heap memory size which will avoid GC scans frequently

[@hritiksharma7154]

@@rajasdataengineering7585 can you please tell me what command I need to write for increasing heap memory size in azure databricks cluster and where as well in spark config ?

[@harshitagrwal9975]

It can only be used for streaming data ?

[@rajasdataengineering7585]

It's mainly used for incremental load both streaming and batch processing

[@oiwelder]

Sir, could you create content explaining Airflow with pyspark?

[@rajasdataengineering7585]

Hi Welder, sure will create bro

[@andrejbelak9936]

Great video, can you share the example notebook please

[@BRO_B23]

Can you please make a video on Job creation how to configure variables\parameters using notebook to deploy one environment to another environment (i.e. Dev to UAT or UAT to Prod) ? Also, make a video on custom logging mechanism to capture the success\failure for each notebook? if you share these it will be helpful.

[@rajasdataengineering7585]

I have already created a video on jobs and workflows kzbin.info/www/bejne/hXXUk5Rvd6aDrNUsi=xBVq9XEfgxAaiZ9u It is covering few aspects in your requirement and will create another video covering all aspects of your requirement

[@sreevidyaVeduguri]

Can we use auto loader for delta tables in Databricks

[@rajasdataengineering7585]

Yes we can use

[@riyazbasha8623]

Will you take online class on data engineer

[@lucaslira5]

can you make a video using auto loader + forechBatch please? using merge

[@rajasdataengineering7585]

Sure, wi create a video on this requirement

[@ADFTrainer]

Where can we find script

[@ankitsaxena565]

Sir , please share the spark full play list

[@rajasdataengineering7585]

kzbin.info/aero/PLgPb8HXOGtsQeiFz1y9dcLuXjRh8teQtw

[@sambitmohanty1758]

Hi can you make a video on a project which includes complete implementation not like which is there in your playlist

[@rajasdataengineering7585]

Hi, sure will create

[@anantababa]

nice one ,can you share code notebook

[@bhargaviakkineni]

Sir could you please make a video on zip and zipwithindex requesting

[@rajasdataengineering7585]

Hi Bhargavi, sure will create a video on this requirement

[@SujeetKumarMehta-w7m]

We want to interact with you. Please come once in virtual meeting. We are great fan of You.❤

[@sohaibshah1771]

Size of the video is too high.

[@rajasdataengineering7585]

Are you downloading the video?

[@sohaibshah1771]

@@rajasdataengineering7585 thanks for reply, Not really, I am talking about watching duration.

[@rajasdataengineering7585]

@sohaibshah1771 oh ok. It is needed actually to explain the concepts properly