Відео

declare @Player table (PlayerId int, PlayerName varchar(10)) insert into @Player values (1,'Nadal'),(2,'Federer'),(3,'Novak') declare @Matches table (Year int, Wimbledon tinyint,Fr_Open tinyint, US_Open tinyint, Au_Open tinyint) insert into @Matches values (2017, 2,1,1,2),(2018,3,1,3,2),(2019,3,1,1,3) select P.PlayerId, P.PlayerName , count ( distinct W.Year ) as Wimbledon , count ( distinct F.Year ) Fr_Open , count ( distinct U.Year ) as Us_Open , count ( distinct A.Year ) as Au_Open , count ( distinct W.Year ) + count ( distinct F.Year )+ count ( distinct U.Year ) + count ( distinct A.Year ) as Total_Grand_Slams from @Player P left join @Matches W ON P.PlayerId = W.Wimbledon left join @Matches F ON P.PlayerId = F.Fr_Open left join @Matches U ON P.PlayerId = U.US_Open left join @Matches A ON P.PlayerId = A.Au_Open group by P.PlayerId, P.PlayerName order by P.PlayerId

Great, thank you. You have explained in simpler way to understand anyone.

A Passionate teacher,,,Hats off...Keep updating ...this is like contribution to Indians growth...Heart felt thanks

Hi Sir, we want vidoe for performance issues and solutions while develope the notebook what are the issue comes

Is it required to learn Delta Live table for 3 year exp person to switch to data engineer role ?

Use window function row_number, then use filter to filter out row nums from 11 to 20: w=Window.orderby(lit("A")) df.withColumn("ROWNUM", row_number().over(w)).filter( (col("ROWNUM")<11) | col("ROWNUM")>20) ).drop("ROWNUM").show()

can i get files which your are worked for demo

Thanks for this video, But I am curious why didnt you directly use min max with group by which would have fetched the same result ``` result = df.withColumn("event_date", F.to_date("event_date")) \ .groupBy("event_status") \ .agg( F.min("event_date").alias("event_start_date"), F.max("event_date").alias("event_end_date") ) \ .orderBy("event_start_date") result.show() ```

Please make Video on Salting in Performance optimization

Awesome work bro. Have you put these notebooks somewhere in your github? Can you share that with us if possible?

Finally found one person who can explain Broadcast variable in a clear and understandable way. Huge respect bro. Subscribed and off I go to other videos in the playlist :)

You are a great teacher.

Very good video, thank you

thank you sir

Excellent job. Can you please provide me the data set and code? Or please give me the Git link to download the dataset and code for your tutorials. Thanks.

Thanks for the content!

Please make video on liquid clustering..

The file was shared at the beginning is incorrect , it has an extra comma delimater which cause all columns to be added to _corrupt_record

Awesome explanation on Z-ordering. Greatly appreciated your efforts making this video.

BEST MEANS BEST VIDEO EVER IF YOU ARE INTERESED TO LEARN THEN .

at least you should have make one video on how to open databricks notebook

so helpful ..thanks for helping the community

Where can I find the datasets used in this demo? is there any github repo you can share?

how to explode two column at the same time getting error in below code brand=[('Raja',["TV","Oven","Ref","AC"],["Scooter","Car"]), ('supriya',["AC","Washimach",None],["Car",None]) ] df_app=spark.createDataFrame(data=brand,schema=['name','appliances','vehicles']) df_explode=df_app.select(df_app.name,explode(df_app.appliances),explode(df_app.vehicles))

add more videos on this delta live tables

Hi Raja ,please do azure synapse analytics,eagerly waiting

Superb explanation Raja 👌 👏 👍

Are any prerequisites required to this pyspark series?

Very Nice

thanks for your vides as DLT is but confusing topic for me, can you create a video on DLT constraint in SQL and Python in this DLT series

Keep going

sir plz explain about cluster mode vs client mode

Thanks alot for in depth explanation😊

union_df = call_df.select("from_id", "to_id", "duration").unionAll(call_df.select("to_id", "from_id", "duration")) ######################################################################################################################### final_df= (union_df.filter(F.col("from_id") < F.col("to_id")) .groupBy(F.col("from_id").alias("person_1"), F.col("to_id").alias("person_2")) .agg(F.sum(F.col("duration")).alias("total_duration"), F.count(F.lit(1)).alias("total_calls"))) ######################################################################################################################### final_df.display()

input_data = [("01-06-2020", 'Won'), ("02-06-2020", 'Won'), ("03-06-2020", 'Won'), ("04-06-2020", 'Lost'), ("05-06-2020", 'Lost'), ("06-06-2020", 'Lost'), ("07-06-2020", 'Won')] input_schema = "event_date STRING, event_status STRING" df = spark.createDataFrame(data= input_data, schema= input_schema).withColumn("event_date", F.to_date(F.col("event_date"), "dd-MM-yyyy")) ##################################### windowSpec= Window.partitionBy(F.col("event_status")).orderBy(F.col("event_date")) rnk_df= df.withColumn("rnk", F.row_number().over(windowSpec)) ##################################### final_df= rnk_df.withColumn('grp_id',F.dayofmonth(F.col("event_date")) - F.col("rnk")) ##################################### result_df = (final_df.groupBy(F.col("grp_id"), F.col("event_status")).agg(F.max(F.col("event_status")).alias("eventstatus"),F.min(F.col("event_date")).alias("start_date"), F.max(F.col("event_date")).alias("end_date")).drop(F.col("grp_id"), F.col("event_status")) ) result_df.display()

Sir, Your explanations are very clear & concise. Thank you

Hi sir I don't understand use of spot instance?

As always, well explained and very useful. Thank you!

You explained it so simply... i hope will be able to explain to the interviewer the same way u did😅

awsome

Hi Raja, is there anyway to get data sets / code which you are explaining for practice

Good video Raja. In real time we don’t know exact versions how can we deal with them dynamically ?

Invaluable explanation sir! I went through many blogs but couldn't get it. You made it crystal clear😊

Great Explanation and You covered all topics which will help in interview and real time projects. Thanks for your effort...

Some of videos are not showing,is it paid one ,can you please let us know

Hi sir, where can i get notebook for the classes. could you please share

can we attend daily classes !

A higher order function is a function that takes one or more functions as arguments, or returns a function as its result.

Crystals clear Explanation...very much helpful

Very nice explanations. thanks