DBMS · Architecture & Theory interview questions

1. A.the ANSI-SPARC design separating external, conceptual and internal views of data
2. B.the community-level logical description of the whole database structure and constraints
3. C.the relational algebra operation combining tuples that agree on common attributes
4. D.the user-level view describing how a particular group of users sees the data

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1. A.Logical data independence
2. B.CAP theorem
3. C.NoSQL database
4. D.Three-schema architecture

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1. A.Three-schema architecture — the relational algebra operation that filters tuples satisfying a given predicate
2. B.Three-schema architecture — the ANSI-SPARC design separating external, conceptual and internal views of data
3. C.Three-schema architecture — the relational algebra operation returning tuples present in either of two compatible relations
4. D.Three-schema architecture — the principle that a distributed store cannot guarantee consistency, availability and partition tolerance together

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1. A.the community-level logical description of the whole database structure and constraints
2. B.the person responsible for the schema, security, performance and backups of a database
3. C.the principle that a distributed store cannot guarantee consistency, availability and partition tolerance together
4. D.the user-level view describing how a particular group of users sees the data

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1. A.CAP theorem
2. B.Internal schema
3. C.External schema
4. D.Data abstraction

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1. A.External schema — a non-relational store favoring flexible schemas and horizontal scaling over strict joins
2. B.External schema — the principle that a distributed store cannot guarantee consistency, availability and partition tolerance together
3. C.External schema — the user-level view describing how a particular group of users sees the data
4. D.External schema — the relational algebra operation combining tuples that agree on common attributes

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1. A.the relational algebra operation that filters tuples satisfying a given predicate
2. B.the community-level logical description of the whole database structure and constraints
3. C.a non-relational store favoring flexible schemas and horizontal scaling over strict joins
4. D.hiding storage and implementation details so users interact with data at a higher level

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1. A.Conceptual schema
2. B.Internal schema
3. C.Union operator
4. D.NoSQL database

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1. A.Conceptual schema — the duplication of the same data in multiple places, a key drawback of file-based systems
2. B.Conceptual schema — the principle that a distributed store cannot guarantee consistency, availability and partition tolerance together
3. C.Conceptual schema — a non-relational store favoring flexible schemas and horizontal scaling over strict joins
4. D.Conceptual schema — the community-level logical description of the whole database structure and constraints

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1. A.a non-relational store favoring flexible schemas and horizontal scaling over strict joins
2. B.the ability to change the conceptual schema without altering external views or applications
3. C.the relational algebra operation that keeps only specified columns of a relation
4. D.the physical storage description of how data is actually stored on disk

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1. A.Natural join operator
2. B.NoSQL database
3. C.Data abstraction
4. D.Internal schema

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1. A.Internal schema — the physical storage description of how data is actually stored on disk
2. B.Internal schema — the ANSI-SPARC design separating external, conceptual and internal views of data
3. C.Internal schema — a non-relational store favoring flexible schemas and horizontal scaling over strict joins
4. D.Internal schema — the relational algebra operation that keeps only specified columns of a relation

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1. A.the ability to change the conceptual schema without altering external views or applications
2. B.the user-level view describing how a particular group of users sees the data
3. C.the community-level logical description of the whole database structure and constraints
4. D.the person responsible for the schema, security, performance and backups of a database

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1. A.Logical data independence
2. B.Data redundancy
3. C.Data abstraction
4. D.Conceptual schema

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1. A.Logical data independence — the user-level view describing how a particular group of users sees the data
2. B.Logical data independence — the community-level logical description of the whole database structure and constraints
3. C.Logical data independence — the principle that a distributed store cannot guarantee consistency, availability and partition tolerance together
4. D.Logical data independence — the ability to change the conceptual schema without altering external views or applications

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1. A.the user-level view describing how a particular group of users sees the data
2. B.the ANSI-SPARC design separating external, conceptual and internal views of data
3. C.hiding storage and implementation details so users interact with data at a higher level
4. D.the ability to change physical storage without altering the conceptual schema

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1. A.Database administrator
2. B.Physical data independence
3. C.Projection operator
4. D.Logical data independence

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1. A.Physical data independence — the ability to change physical storage without altering the conceptual schema
2. B.Physical data independence — the person responsible for the schema, security, performance and backups of a database
3. C.Physical data independence — the physical storage description of how data is actually stored on disk
4. D.Physical data independence — hiding storage and implementation details so users interact with data at a higher level

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1. A.the user-level view describing how a particular group of users sees the data
2. B.the duplication of the same data in multiple places, a key drawback of file-based systems
3. C.the person responsible for the schema, security, performance and backups of a database
4. D.the principle that a distributed store cannot guarantee consistency, availability and partition tolerance together

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1. A.CAP theorem
2. B.Database administrator
3. C.Projection operator
4. D.Physical data independence

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1. A.Database administrator — the person responsible for the schema, security, performance and backups of a database
2. B.Database administrator — the ANSI-SPARC design separating external, conceptual and internal views of data
3. C.Database administrator — a non-relational store favoring flexible schemas and horizontal scaling over strict joins
4. D.Database administrator — the relational algebra operation combining tuples that agree on common attributes

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1. A.the relational algebra operation that keeps only specified columns of a relation
2. B.the relational algebra operation that filters tuples satisfying a given predicate
3. C.the duplication of the same data in multiple places, a key drawback of file-based systems
4. D.the ability to change the conceptual schema without altering external views or applications

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1. A.External schema
2. B.Conceptual schema
3. C.Projection operator
4. D.Selection operator

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1. A.Selection operator — the user-level view describing how a particular group of users sees the data
2. B.Selection operator — the relational algebra operation that filters tuples satisfying a given predicate
3. C.Selection operator — the principle that a distributed store cannot guarantee consistency, availability and partition tolerance together
4. D.Selection operator — the physical storage description of how data is actually stored on disk

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1. A.the relational algebra operation that keeps only specified columns of a relation
2. B.the user-level view describing how a particular group of users sees the data
3. C.the principle that a distributed store cannot guarantee consistency, availability and partition tolerance together
4. D.hiding storage and implementation details so users interact with data at a higher level

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1. A.Internal schema
2. B.Database administrator
3. C.Projection operator
4. D.Natural join operator

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1. A.Projection operator — the relational algebra operation that keeps only specified columns of a relation
2. B.Projection operator — hiding storage and implementation details so users interact with data at a higher level
3. C.Projection operator — the principle that a distributed store cannot guarantee consistency, availability and partition tolerance together
4. D.Projection operator — a non-relational store favoring flexible schemas and horizontal scaling over strict joins

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1. A.the relational algebra operation combining tuples that agree on common attributes
2. B.hiding storage and implementation details so users interact with data at a higher level
3. C.the duplication of the same data in multiple places, a key drawback of file-based systems
4. D.the person responsible for the schema, security, performance and backups of a database

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1. A.Physical data independence
2. B.Conceptual schema
3. C.Natural join operator
4. D.Union operator

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1. A.Natural join operator — the physical storage description of how data is actually stored on disk
2. B.Natural join operator — the community-level logical description of the whole database structure and constraints
3. C.Natural join operator — the relational algebra operation combining tuples that agree on common attributes
4. D.Natural join operator — the relational algebra operation returning tuples present in either of two compatible relations

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