In this video we will solve an interesting pyspark interview question. Here is the script:
from pyspark.sql.types import *
from pyspark.sql.functions import *
schema = StructType([
StructField("team_1", StringType(), True),
StructField("team_2", StringType(), True),
StructField("winner", StringType(), True)
])
data = [
("India", "SL", "India"),
("SL", "Aus", "Aus"),
("SA", "Eng", "Eng"),
("Eng", "NZ", "NZ"),
("Aus", "India", "India"),
("Eng", "Aus", "DRAW")
]
df = spark.createDataFrame(data, schema)
Zero to hero(Advance) SQL Aggregation:
https://youtu.be/5Ighj_2PGV0
Most Asked Join Based Interview Question:
https://youtu.be/xR87ctOgpAE
Solving 4 Trick SQL problems:
https://youtu.be/Ck1gQrlS5pQ
Data Analyst Spotify Case Study:
https://youtu.be/-YdAIMjHZrM
Top 10 SQL interview Questions:
https://youtu.be/Iv9qBz-cyVA
Interview Question based on FULL OUTER JOIN:
https://youtu.be/KQfWd6V3IB8
Playlist to master SQL :
https://youtube.com/playlist?list=PLBTZqjSKn0IeKBQDjLmzisazhqQy4iGkb
Rank, Dense_Rank and Row_Number:
https://youtu.be/xMWEVFC4FOk
#pyspark #dataengineer
