Solve using PySpark and Spark-SQL | Accenture Interview Question |

[@JyotiKumari-zu2vu]

How can i purchase your delta lake course

[@GeekCoders]

www.geekcoders.co.in/courses/Build-Real-Time-DeltaLake-Project--using-PySpark-and-Spark-SQL-with-Databricks-64a0af30e4b0f71237fa1bf3-64a0af30e4b0f71237fa1bf3

[@fit1801]

Bro can you please tell me which software you are using to record screen.

[@RajeshKumar-re8tj]

Hey Sagar, Please make delta live table related project. Delta live table is most demanding.

[@GeekCoders]

Sure will do that soon thanks

[@vikaschavan6118]

I saw this question on leetcode sql question series.

[@SzalonyEdek]

Cool. The second syntax is DataFrame, not PySpark, as a Pyspark it could be also DataSet or RDD

[@GeekCoders]

Second query is dataframe only

[@rawat7203]

Thank you Sir

[@caferacerkid]

result_df = df.filter((col("ID") % 2 != 0) & (col("description") != 'boring')).orderBy(desc("rating")) display(result_df)

[@SomwritaDe]

from pyspark.sql.functions import col, upper df_1 = df.where(df.id%2!=0).where(upper(df.description)!="BORING") display(df_1)

[@AmitSingh-e6m]

my Solution: df.select("*").filter((col("ID") % 2 != 0) & (col("description") != "boring")).orderBy("rating",ascending=False)