Cognitive Class: SQL Access for Hadoop Exam Answers 2021

Cognitive Class: SQL Access for Hadoop Exam Answers 2021

Hadoop and SQL are also data management systems, but they do so in different ways. Hadoop is a software platform, while SQL is a programming language. Both methods have advantages and disadvantages when it comes to big data. Mongodb is capable of handling larger data sets by only writing data once. Big SQL is a massively parallel processing (MPP) SQL engine that runs directly on a physical Hadoop Distributed File System (HDFS) cluster for versions 3.0 and later. Big SQL makes use of a low-latency parallel execution infrastructure that reads and writes Hdfs data natively. The Big SQL head coordinates SQL query processing with the workers, who are in charge of the majority of HDFS data access and processing.

1. In order to use Big SQL, you need to learn several new query languages. True or false?

  1. True
  2. False

2. Which component serves as the main interface between Big SQL and Hadoop?

  1. Hive Metastore
  2. Big SQL Master Node
  3. Scheduler
  4. Big SQL Worker Node
  5. UDF FMP

3. Officially, there are two different releases of Big SQL. True or false?

  1. True
  2. False

4. Which of the following statements is true of a partitioned table?

  1. Query predicates can be used to avoid scanning every partition
  2. A table may be partitioned on one or more rows
  3. Data is stored in multiple directories for each partition
  4. The partitions are specified only when data is inserted
  5. All of the above

5. Which of the following statements is true of JSqsh?

  1. JSqsh supports multiple active sessions
  2. JSqsh is an open source command client
  3. JSqsh can be used to work with Big SQL
  4. The term JSqsh derives from “Java SQL Shell”
  5. All of the above

6. Which of the following statements is true of the SQL data type?

  1. The database  engine supports the SQL data type
  2. There are more declared data types than SQL data types
  3. SQL data types are provided in the CREATE statement
  4. SQL data types tell SerDe how to encode and decode values
  5. All of the above

7. In Big SQL, the STRING and VARCHAR types are equivalent and can be used interchangeably. True or false?

  1. True
  2. False

8.What is the default Big SQL schema?

  1. “admin”
  2. Your login name
  3. “warehouse”
  4. “default”
  5. The schema that was previously used

9. Which of the following statements are true of Parquet files? Select all that apply.

  1. Parquet files are supported by the native I/O engine
  2. Parquet files provide a columnar storage format
  3. Parquet files support the DATE and TIMESTAMP data types
  4. Parquet is a high-performance file format
  5. Parquet files are good for data interchange outside of Hadoop

10. Which of the following statements are true of ORC files? Select all that apply.

  1. ORC files are supported by the native I/O engine
  2. ORC files are good for data interchange outside of Hadoop
  3. Individual columns can be retrieved efficiently
  4. ORC files can be efficiently compressed
  5. Big SQL can exploit every advanced ORC feature

11. Which of the following statements is NOT true of the Native I/O processing engine?

  1. There is a high-speed interface for common file formats
  2. The native engine supports the delimited file format, among others
  3. The native engine is highly optimized and parallelized
  4. The native engine is written in Java
  5. All of the above statements are true

12. Which of the following statements about Big SQL are true? Select all that apply.

  1. Big SQL comes with comprehensive SQL support
  2. Big SQL provides a powerful SQL query rewriter
  3. Big SQL currently doesn’t support subqueries
  4. Big SQL queries can only be written for one data source
  5. Big SQL supports all the standard join operations

13. Which keyword indicates that the data in a table is not managed by the database manager?

  1. USE
  2. LOCATION
  3. EXTERNAL
  4. HADOOP
  5. CHECK

14. The Avro file format is more efficient than Parquet and ORC. True or false?

  1. True
  2. False

15. Which statement accurately characterizes the Big SQL data types?

  1. Sequence files are the fastest format
  2. Delimited files are the most efficient format
  3. ORC files can be efficiently compressed
  4. Avro is human readable
  5. RC files replaced ORC files

16. Which Big SQL architecture component is responsible for accepting queries?

  1. Hive Server
  2. Scheduler
  3. Worker Node
  4. DDL Processing Engine
  5. Master Node

17. Big SQL differs from Big SQL v1 in which of the following ways? Select all that apply.

  1. Big SQL does not have support for HBase
  2. Big SQL v1 reserves double quotes for identifiers
  3. Big SQL requires the HADOOP keyword for table creation
  4. Big SQL v1 treats single and double quotes as the same
  5. DDL in Big SQL v1 is a superset of Big SQL

18. In Big SQL, what is the term for the default directory in the distributed file system (DFS) where tables are stored?

  1. Schema
  2. Metastore
  3. Table
  4. Warehouse
  5. Partitioned Table

19. What are the main data type categories in Big SQL? Select all that apply.

  1. SQL
  2. INT
  3. Declared
  4. REAL
  5. Hive

20. When creating a table, which keyword is used to specify the DFS directory for storing data files?

  1. EXTERNAL
  2. HADOOP
  3. USE
  4. CHECK
  5. LOCATION

21. Which human-readable Big SQL file format uses a character to separate column values?

  1. Avro
  2. Parquet
  3. ORC
  4. Sequence
  5. Delimited

The Distributed File System (DFS) is a collection of client and server services that allow an organisation to organise several distributed SMB file shares into a distributed file system using Microsoft Windows servers. Location transparency (via the namespace component) and redundancy are two components of DFS’s operation (via the file replication component). By allowing shares in multiple locations to be logically grouped under one folder, the “DFS root,” these components increase data availability in the event of failure or heavy load.

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