Cognitive Class: SQL Access for Hadoop Exam Answers

Cognitive Class: SQL Access for Hadoop Exam Answers: ✅✅✅ There is no learning curve here. Big SQL is about applying SQL to your existing data – there are no proprietary storage formats. Big SQL is another tool to work with your Hadoop data. Big SQL provides a common and familiar syntax for those that are already using SQL with their relational data to work with their big data.

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Course NameSQL Access for Hadoop
TrainerHenry L. Quach
OrganizationCognitive Class
AudienceAnalysts, developers, and administrators who are interested in using SQL access on their Hadoop data.
LevelIntermediate
LanguageEnglish
PriceFree

Cognitive Class – SQL Access for Hadoop Answers

Cognitive Class: SQL Access for Hadoop Exam Answers

Module 1: Big SQL Overview SQL Access for Hadoop

1. 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

2. 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

3. 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

Module 2: Big SQL data types

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

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

2. 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

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

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

SQL Access for Hadoop Final Exam Answers

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

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