Associate-Developer-Apache-Spark試験無料問題集「Databricks Certified Associate Developer for Apache Spark 3.0 認定」
Which of the following code blocks returns a DataFrame with a single column in which all items in column attributes of DataFrame itemsDf are listed that contain the letter i?
Sample of DataFrame itemsDf:
1.+------+----------------------------------+-----------------------------+-------------------+
2.|itemId|itemName |attributes |supplier |
3.+------+----------------------------------+-----------------------------+-------------------+
4.|1 |Thick Coat for Walking in the Snow|[blue, winter, cozy] |Sports Company Inc.|
5.|2 |Elegant Outdoors Summer Dress |[red, summer, fresh, cooling]|YetiX |
6.|3 |Outdoors Backpack |[green, summer, travel] |Sports Company Inc.|
7.+------+----------------------------------+-----------------------------+-------------------+
Sample of DataFrame itemsDf:
1.+------+----------------------------------+-----------------------------+-------------------+
2.|itemId|itemName |attributes |supplier |
3.+------+----------------------------------+-----------------------------+-------------------+
4.|1 |Thick Coat for Walking in the Snow|[blue, winter, cozy] |Sports Company Inc.|
5.|2 |Elegant Outdoors Summer Dress |[red, summer, fresh, cooling]|YetiX |
6.|3 |Outdoors Backpack |[green, summer, travel] |Sports Company Inc.|
7.+------+----------------------------------+-----------------------------+-------------------+
正解：C
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The code block displayed below contains an error. The code block should merge the rows of DataFrames transactionsDfMonday and transactionsDfTuesday into a new DataFrame, matching column names and inserting null values where column names do not appear in both DataFrames. Find the error.
Sample of DataFrame transactionsDfMonday:
1.+-------------+---------+-----+-------+---------+----+
2.|transactionId|predError|value|storeId|productId| f|
3.+-------------+---------+-----+-------+---------+----+
4.| 5| null| null| null| 2|null|
5.| 6| 3| 2| 25| 2|null|
6.+-------------+---------+-----+-------+---------+----+
Sample of DataFrame transactionsDfTuesday:
1.+-------+-------------+---------+-----+
2.|storeId|transactionId|productId|value|
3.+-------+-------------+---------+-----+
4.| 25| 1| 1| 4|
5.| 2| 2| 2| 7|
6.| 3| 4| 2| null|
7.| null| 5| 2| null|
8.+-------+-------------+---------+-----+
Code block:
sc.union([transactionsDfMonday, transactionsDfTuesday])
Sample of DataFrame transactionsDfMonday:
1.+-------------+---------+-----+-------+---------+----+
2.|transactionId|predError|value|storeId|productId| f|
3.+-------------+---------+-----+-------+---------+----+
4.| 5| null| null| null| 2|null|
5.| 6| 3| 2| 25| 2|null|
6.+-------------+---------+-----+-------+---------+----+
Sample of DataFrame transactionsDfTuesday:
1.+-------+-------------+---------+-----+
2.|storeId|transactionId|productId|value|
3.+-------+-------------+---------+-----+
4.| 25| 1| 1| 4|
5.| 2| 2| 2| 7|
6.| 3| 4| 2| null|
7.| null| 5| 2| null|
8.+-------+-------------+---------+-----+
Code block:
sc.union([transactionsDfMonday, transactionsDfTuesday])
正解：E
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解説: (GoShiken メンバーにのみ表示されます)
Which of the following code blocks produces the following output, given DataFrame transactionsDf?
Output:
1.root
2. |-- transactionId: integer (nullable = true)
3. |-- predError: integer (nullable = true)
4. |-- value: integer (nullable = true)
5. |-- storeId: integer (nullable = true)
6. |-- productId: integer (nullable = true)
7. |-- f: integer (nullable = true)
DataFrame 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.+-------------+---------+-----+-------+---------+----+
Output:
1.root
2. |-- transactionId: integer (nullable = true)
3. |-- predError: integer (nullable = true)
4. |-- value: integer (nullable = true)
5. |-- storeId: integer (nullable = true)
6. |-- productId: integer (nullable = true)
7. |-- f: integer (nullable = true)
DataFrame 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.+-------------+---------+-----+-------+---------+----+
正解：E
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解説: (GoShiken メンバーにのみ表示されます)
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')
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')
正解：D
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解説: (GoShiken メンバーにのみ表示されます)