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Questions and Answers
Data Modeling is an important part of database design.
Data Modeling is an important part of database design.
True
Traditional relational databases rely on denormalized tables with foreign keys and support table joins.
Traditional relational databases rely on denormalized tables with foreign keys and support table joins.
False
In Cassandra, data modeling follows a query-driven approach, optimized for specific data access patterns.
In Cassandra, data modeling follows a query-driven approach, optimized for specific data access patterns.
True
Cassandra is a traditional relational database.
Cassandra is a traditional relational database.
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Cassandra's data modeling is based on data access patterns and application queries.
Cassandra's data modeling is based on data access patterns and application queries.
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In Cassandra, queries are designed to access multiple tables for faster data retrieval.
In Cassandra, queries are designed to access multiple tables for faster data retrieval.
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Denormalization and data duplication are key elements for improving performance in Cassandra.
Denormalization and data duplication are key elements for improving performance in Cassandra.
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Which of these are not components of Cassandra data model?
Which of these are not components of Cassandra data model?
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Keyspaces in Cassandra serve as data containers and are similar to schemas in traditional databases.
Keyspaces in Cassandra serve as data containers and are similar to schemas in traditional databases.
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Replication in Cassandra is configured and applied at the column level.
Replication in Cassandra is configured and applied at the column level.
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In Cassandra, columns can have different data types, including text, float, double, and counter
In Cassandra, columns can have different data types, including text, float, double, and counter
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Tables in Cassandra are created inside keyspaces, and they are designed to support denormalization for efficient querying.
Tables in Cassandra are created inside keyspaces, and they are designed to support denormalization for efficient querying.
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Data duplication is not recommended in Cassandra as it increases storage costs and can lead to data inconsistency.
Data duplication is not recommended in Cassandra as it increases storage costs and can lead to data inconsistency.
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Every table in Cassandra must have a primary key for unique row identification.
Every table in Cassandra must have a primary key for unique row identification.
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Cassandra operates within a cluster of interconnected machines, but each cluster has only one node for performance optimization.
Cassandra operates within a cluster of interconnected machines, but each cluster has only one node for performance optimization.
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In Cassandra, data is arranged and distributed in a ring pattern, ensuring a circular flow of data across nodes.
In Cassandra, data is arranged and distributed in a ring pattern, ensuring a circular flow of data across nodes.
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Cassandra uses a secondary key for unique row identification, which comprises a partition key and optional clustering columns.
Cassandra uses a secondary key for unique row identification, which comprises a partition key and optional clustering columns.
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The partition key in Cassandra determines the specific data access pattern and defines the way data is distributed among nodes.
The partition key in Cassandra determines the specific data access pattern and defines the way data is distributed among nodes.
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Clustering columns are used to arrange data within each partition, ensuring a sorted and consistent order of rows.
Clustering columns are used to arrange data within each partition, ensuring a sorted and consistent order of rows.
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In Cassandra, a partition is a set of rows with unique data points and does not share the same partition key.
In Cassandra, a partition is a set of rows with unique data points and does not share the same partition key.
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Partitions in Cassandra represent a physical unit of access, ensuring that data is retrieved from a single location for fast access.
Partitions in Cassandra represent a physical unit of access, ensuring that data is retrieved from a single location for fast access.
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Cassandra optimizes queries by arranging rows within partitions based on the values of clustering columns.
Cassandra optimizes queries by arranging rows within partitions based on the values of clustering columns.
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One of Cassandra's performance optimizations involves having as many partitions as possible to ensure faster read and write operations.
One of Cassandra's performance optimizations involves having as many partitions as possible to ensure faster read and write operations.
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Which rule of Cassandra data modeling states that it is beneficial to have as few partitions as possible for faster read performance?
Which rule of Cassandra data modeling states that it is beneficial to have as few partitions as possible for faster read performance?
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The rule "Maximize Data Duplications" ensures that Cassandra uses data redundancy within the clusters for high availability and to prevent data loss.
The rule "Maximize Data Duplications" ensures that Cassandra uses data redundancy within the clusters for high availability and to prevent data loss.
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The rule "Spread Data Evenly" emphasizes the balanced distribution of data across all cluster nodes for performance optimization and resilience.
The rule "Spread Data Evenly" emphasizes the balanced distribution of data across all cluster nodes for performance optimization and resilience.
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The rule "Create Tables Based on Queries" recommends designing tables based on the specific queries that will be used to access them.
The rule "Create Tables Based on Queries" recommends designing tables based on the specific queries that will be used to access them.
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Which of these is NOT a common type of database relationship?
Which of these is NOT a common type of database relationship?
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A one-to-one relationship means that there is a direct and unique correspondence between two entities, with each entity linked to a single instance of the other entity.
A one-to-one relationship means that there is a direct and unique correspondence between two entities, with each entity linked to a single instance of the other entity.
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A one-to-many relationship means that a single instance of one entity can be associated with multiple instances of another entity.
A one-to-many relationship means that a single instance of one entity can be associated with multiple instances of another entity.
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A many-to-many relationship represents a scenario where multiple instances of one entity can relate to multiple instances of another entity.
A many-to-many relationship represents a scenario where multiple instances of one entity can relate to multiple instances of another entity.
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Study Notes
Data Modeling (IT315)
- Data Modeling is a crucial part of database design
- Traditional relational databases use normalized tables with foreign keys and support table joins
- In Cassandra, data modeling is query-driven, designed for specific data access patterns
Objectives
- Define data model
- Define a keyspace
- Define table and column
- Use basic CQL
Cassandra Query-centered Approach
- Cassandra is not a traditional relational database
- Data modeling is based on data access patterns and application queries
- Queries are structured to visit a single table for fast data access
- Denormalization and data duplication are key for performance
Cassandra Data Model Components
- Keyspace
- Table
- Column
Keyspace
- Keyspaces are like schemas in traditional databases
- They serve as data containers
- Replication is configured at the keyspace level
- Each table belongs to a keyspace
- Tables in Cassandra are created within keyspaces
- Denormalization is essential; each table should support specific queries
- Data duplication ensures high read performance
- Tables have a primary key for unique row identification
Column
- Columns in Cassandra tables are defined based on data requirements
- Various data types are available, including text, float, double, etc.
- Special columns like Counter are used for specific purposes
Cassandra Cluster
- Cassandra operates in a cluster of interconnected machines
- Each cluster has multiple nodes for fault tolerance
- Data is distributed and arranged in a ring pattern
Primary Key
- In Cassandra, a row is uniquely identified by its primary key
- The primary key includes a partition key and optional clustering columns
- Partition key determines data distribution
- Clustering columns affect data arrangement within a partition
Partition Key
- One or more columns make up the partition key component of the primary key
- Cassandra concatenates all values from the partition key columns to quickly find a partition inside the cluster
- Cassandra divides incoming data into discrete parts and distributes them among cluster nodes by hashing a data property known as the partition key
Partition
- A set of rows (a relatively small subset of the table) that share the same partition key is referred to as a partition
- Since a partition represents a physical unit of access, Cassandra will swiftly fetch all of the rows in a partition at once
- Partitions can be viewed as the outcomes of previously performed queries
Clustering Column
- Cassandra arranges the rows within a partition based on the values of the clustering columns
- Cassandra can swiftly search the partition for a certain row within the partition by using the values of the clustering column during a query
Rules
- Maximize Writes: Cassandra is optimized for fast writes; maximize writes for better read performance
- Maximize Data Duplications: Denormalization and data duplication ensure high availability
- Spread Data Evenly: Distribute data evenly among cluster nodes for balanced performance
- Minimize Partitions Read: Fewer partitions read mean faster queries
- Create Tables Based on Queries: Design tables based on the queries they need to support
Relationships
- One-to-one (1:1)
- One-to-many (1:M)
- Many-to-many (M:N)
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Description
Explore the essentials of data modeling in Cassandra as part of database design in IT315. Learn about keyspaces, tables, columns, and the unique query-driven approach that sets Cassandra apart from traditional relational databases. Master the fundamental concepts and components to enhance your understanding of data management in modern applications.
