Try Databricks : Associate-Developer-Apache-Spark practice torrent pass for sure

The code block displayed below contains multiple errors. The code block should return a DataFrame that contains only columns transactionId, predError, value and storeId of DataFrame transactionsDf. Find the errors.
Code block:
transactionsDf.select([col(productId), col(f)])
Sample of transactionsDf:
1.+-------------+---------+-----+-------+---------+----+
2.|transactionId|predError|value|storeId|productId| f|
3.+-------------+---------+-----+-------+---------+----+
4.| 1| 3| 4| 25| 1|null|
5.| 2| 6| 7| 2| 2|null|
6.| 3| 3| null| 25| 3|null|
7.+-------------+---------+-----+-------+---------+----+

• A. The column names should be listed directly as arguments to the operator and not as a list.
• B. The select operator should be replaced by a drop operator, the column names should be listed directly as arguments to the operator and not as a list, and all col() operators should be removed.
• C. The select operator should be replaced by a drop operator, the column names should be listed directly as arguments to the operator and not as a list, and all column names should be expressed as strings without being wrapped in a col() operator.
• D. The column names should be listed directly as arguments to the operator and not as a list and following the pattern of how column names are expressed in the code block, columns productId and f should be replaced by transactionId, predError, value and storeId.
• E. The select operator should be replaced by a drop operator.

The code block displayed below contains an error. The code block should return a DataFrame where all entries in column supplier contain the letter combination et in this order. Find the error.
Code block:
itemsDf.filter(Column('supplier').isin('et'))

• A. Instead of isin, it should be checked whether column supplier contains the letters et, so isin should be replaced with contains. In addition, the column should be accessed using col['supplier'].
• B. The expression only returns a single column and filter should be replaced by select.
• C. The Column operator should be replaced by the col operator and instead of isin, contains should be used.
• D. The expression inside the filter parenthesis is malformed and should be replaced by isin('et', 'supplier').

The code block displayed below contains at least one error. The code block should return a DataFrame with only one column, result. That column should include all values in column value from DataFrame transactionsDf raised to the power of 5, and a null value for rows in which there is no value in column value. Find the error(s).
Code block:
1.from pyspark.sql.functions import udf
2.from pyspark.sql import types as T
3.
4.transactionsDf.createOrReplaceTempView('transactions')
5.
6.def pow_5(x):
7. return x**5
8.
9.spark.udf.register(pow_5, 'power_5_udf', T.LongType())
10.spark.sql('SELECT power_5_udf(value) FROM transactions')

• A. The pow_5 method is unable to handle empty values in column value, the UDF function is not registered properly with the Spark driver, and the name of the column in the returned DataFrame is not result.
• B. The pow_5 method is unable to handle empty values in column value and the name of the column in the returned DataFrame is not result.
• C. The returned DataFrame includes multiple columns instead of just one column.
• D. The pow_5 method is unable to handle empty values in column value, the name of the column in the returned DataFrame is not result, and Spark driver does not call the UDF function appropriately.
• E. The pow_5 method is unable to handle empty values in column value, the name of the column in the returned DataFrame is not result, and the SparkSession cannot access the transactionsDf DataFrame.

Which of the following describes characteristics of the Spark UI?

• A. The Scheduler tab shows how jobs that are run in parallel by multiple users are distributed across the cluster.
• B. Via the Spark UI, stage execution speed can be modified.
• C. Some of the tabs in the Spark UI are named Jobs, Stages, Storage, DAGs, Executors, and SQL.
• D. There is a place in the Spark UI that shows the property spark.executor.memory.
• E. Via the Spark UI, workloads can be manually distributed across executors.

Which of the following code blocks returns a copy of DataFrame transactionsDf where the column storeId has been converted to string type?

• A. transactionsDf.withColumn("storeId", col("storeId").cast("string"))
• B. transactionsDf.withColumn("storeId", convert("storeId").as("string"))
• C. transactionsDf.withColumn("storeId", col("storeId").convert("string"))
• D. transactionsDf.withColumn("storeId", convert("storeId", "string"))
• E. transactionsDf.withColumn("storeId", col("storeId", "string"))