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

Write a Pyspark query to report the movies with an odd-numbered ID and a description that is not "boring".Return the result table in descending order by rating.
data=[(1, 'War','great 3D',8.9)
,(2, 'Science','fiction',8.5)
,(3, 'irish','boring',6.2)
,(4, 'Ice song','Fantacy',8.6)
,(5, 'House card','Interesting',9.1)]
schema="ID int,movie string,description string,rating double"
df=spark.createDataFrame(data,schema)
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[@fit1801]

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

[@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

[@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

[@caferacerkid]

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

[@rawat7203]

Thank you Sir

[@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)