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質問 1：
Which of the following code blocks reads in the JSON file stored at filePath, enforcing the schema expressed in JSON format in variable json_schema, shown in the code block below?
Code block:
1.json_schema = """
2.{"type": "struct",
3. "fields": [
4. {
5. "name": "itemId",
6. "type": "integer",
7. "nullable": true,
8. "metadata": {}
9. },
10. {
11. "name": "supplier",
12. "type": "string",
13. "nullable": true,
14. "metadata": {}
15. }
16. ]
17.}
18."""
A. spark.read.json(filePath, schema=schema_of_json(json_schema))
B. spark.read.json(filePath, schema=spark.read.json(json_schema))
C. spark.read.json(filePath, schema=json_schema)
D. spark.read.schema(json_schema).json(filePath)
1.schema = StructType.fromJson(json.loads(json_schema))
2.spark.read.json(filePath, schema=schema)
正解：D
解説: (Pass4Test メンバーにのみ表示されます)
質問 2：
Which is the highest level in Spark's execution hierarchy?
A. Executor
B. Task
C. Stage
D. Slot
E. Job
正解：E
質問 3：
The code block displayed below contains an error. The code block should save DataFrame transactionsDf at path path as a parquet file, appending to any existing parquet file. Find the error.
Code block:
A. save() is evaluated lazily and needs to be followed by an action.
B. The code block is missing a bucketBy command that takes care of partitions.
C. transactionsDf.format("parquet").option("mode", "append").save(path)
D. The mode option should be omitted so that the command uses the default mode.
E. The code block is missing a reference to the DataFrameWriter.
F. Given that the DataFrame should be saved as parquet file, path is being passed to the wrong method.
正解：E
解説: (Pass4Test メンバーにのみ表示されます)
質問 4：
In which order should the code blocks shown below be run in order to read a JSON file from location jsonPath into a DataFrame and return only the rows that do not have value 3 in column productId?
1. importedDf.createOrReplaceTempView("importedDf")
2. spark.sql("SELECT * FROM importedDf WHERE productId != 3")
3. spark.sql("FILTER * FROM importedDf WHERE productId != 3")
4. importedDf = spark.read.option("format", "json").path(jsonPath)
5. importedDf = spark.read.json(jsonPath)
A. 4, 1, 2
B. 4, 1, 3
C. 5, 1, 2
D. 5, 1, 3
E. 5, 2
正解：C
解説: (Pass4Test メンバーにのみ表示されます)
質問 5：
Which of the following describes Spark's way of managing memory?
A. Spark's memory usage can be divided into three categories: Execution, transaction, and storage.
B. Storage memory is used for caching partitions derived from DataFrames.
C. Disabling serialization potentially greatly reduces the memory footprint of a Spark application.
D. Spark uses a subset of the reserved system memory.
E. As a general rule for garbage collection, Spark performs better on many small objects than few big objects.
正解：B
解説: (Pass4Test メンバーにのみ表示されます)
Which of the following code blocks reads in the JSON file stored at filePath, enforcing the schema expressed in JSON format in variable json_schema, shown in the code block below?
Code block:
1.json_schema = """
2.{"type": "struct",
3. "fields": [
4. {
5. "name": "itemId",
6. "type": "integer",
7. "nullable": true,
8. "metadata": {}
9. },
10. {
11. "name": "supplier",
12. "type": "string",
13. "nullable": true,
14. "metadata": {}
15. }
16. ]
17.}
18."""
A. spark.read.json(filePath, schema=schema_of_json(json_schema))
B. spark.read.json(filePath, schema=spark.read.json(json_schema))
C. spark.read.json(filePath, schema=json_schema)
D. spark.read.schema(json_schema).json(filePath)
1.schema = StructType.fromJson(json.loads(json_schema))
2.spark.read.json(filePath, schema=schema)
正解：D
解説: (Pass4Test メンバーにのみ表示されます)
質問 2：
Which is the highest level in Spark's execution hierarchy?
A. Executor
B. Task
C. Stage
D. Slot
E. Job
正解：E
質問 3：
The code block displayed below contains an error. The code block should save DataFrame transactionsDf at path path as a parquet file, appending to any existing parquet file. Find the error.
Code block:
A. save() is evaluated lazily and needs to be followed by an action.
B. The code block is missing a bucketBy command that takes care of partitions.
C. transactionsDf.format("parquet").option("mode", "append").save(path)
D. The mode option should be omitted so that the command uses the default mode.
E. The code block is missing a reference to the DataFrameWriter.
F. Given that the DataFrame should be saved as parquet file, path is being passed to the wrong method.
正解：E
解説: (Pass4Test メンバーにのみ表示されます)
質問 4：
In which order should the code blocks shown below be run in order to read a JSON file from location jsonPath into a DataFrame and return only the rows that do not have value 3 in column productId?
1. importedDf.createOrReplaceTempView("importedDf")
2. spark.sql("SELECT * FROM importedDf WHERE productId != 3")
3. spark.sql("FILTER * FROM importedDf WHERE productId != 3")
4. importedDf = spark.read.option("format", "json").path(jsonPath)
5. importedDf = spark.read.json(jsonPath)
A. 4, 1, 2
B. 4, 1, 3
C. 5, 1, 2
D. 5, 1, 3
E. 5, 2
正解：C
解説: (Pass4Test メンバーにのみ表示されます)
質問 5：
Which of the following describes Spark's way of managing memory?
A. Spark's memory usage can be divided into three categories: Execution, transaction, and storage.
B. Storage memory is used for caching partitions derived from DataFrames.
C. Disabling serialization potentially greatly reduces the memory footprint of a Spark application.
D. Spark uses a subset of the reserved system memory.
E. As a general rule for garbage collection, Spark performs better on many small objects than few big objects.
正解：B
解説: (Pass4Test メンバーにのみ表示されます)
横山** -
短い間お世話になりました。Associate-Developer-Apache-Spark試験無事合格できました。迅速かつ丁寧なご対応ありがとうございました。