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| <article class="doc"> |
| <h1 class="page">Introduction</h1> |
| <div id="preamble"> |
| <div class="sectionbody"> |
| <div class="paragraph"> |
| <p>Apache Cassandra stores data in tables, with each table consisting of |
| rows and columns. CQL (Cassandra Query Language) is used to query the |
| data stored in tables. Apache Cassandra data model is based around and |
| optimized for querying. Cassandra does not support relational data |
| modeling intended for relational databases.</p> |
| </div> |
| </div> |
| </div> |
| <div class="sect1"> |
| <h2 id="what-is-data-modeling"><a class="anchor" href="#what-is-data-modeling"></a>What is Data Modeling?</h2> |
| <div class="sectionbody"> |
| <div class="paragraph"> |
| <p>Data modeling is the process of identifying entities and their |
| relationships. In relational databases, data is placed in normalized |
| tables with foreign keys used to reference related data in other tables. |
| Queries that the application will make are driven by the structure of |
| the tables and related data are queried as table joins.</p> |
| </div> |
| <div class="paragraph"> |
| <p>In Cassandra, data modeling is query-driven. The data access patterns |
| and application queries determine the structure and organization of data |
| which then used to design the database tables.</p> |
| </div> |
| <div class="paragraph"> |
| <p>Data is modeled around specific queries. Queries are best designed to |
| access a single table, which implies that all entities involved in a |
| query must be in the same table to make data access (reads) very fast. |
| Data is modeled to best suit a query or a set of queries. A table could |
| have one or more entities as best suits a query. As entities do |
| typically have relationships among them and queries could involve |
| entities with relationships among them, a single entity may be included |
| in multiple tables.</p> |
| </div> |
| </div> |
| </div> |
| <div class="sect1"> |
| <h2 id="query-driven-modeling"><a class="anchor" href="#query-driven-modeling"></a>Query-driven modeling</h2> |
| <div class="sectionbody"> |
| <div class="paragraph"> |
| <p>Unlike a relational database model in which queries make use of table |
| joins to get data from multiple tables, joins are not supported in |
| Cassandra so all required fields (columns) must be grouped together in a |
| single table. Since each query is backed by a table, data is duplicated |
| across multiple tables in a process known as denormalization. Data |
| duplication and a high write throughput are used to achieve a high read |
| performance.</p> |
| </div> |
| </div> |
| </div> |
| <div class="sect1"> |
| <h2 id="goals"><a class="anchor" href="#goals"></a>Goals</h2> |
| <div class="sectionbody"> |
| <div class="paragraph"> |
| <p>The choice of the primary key and partition key is important to |
| distribute data evenly across the cluster. Keeping the number of |
| partitions read for a query to a minimum is also important because |
| different partitions could be located on different nodes and the |
| coordinator would need to send a request to each node adding to the |
| request overhead and latency. Even if the different partitions involved |
| in a query are on the same node, fewer partitions make for a more |
| efficient query.</p> |
| </div> |
| </div> |
| </div> |
| <div class="sect1"> |
| <h2 id="partitions"><a class="anchor" href="#partitions"></a>Partitions</h2> |
| <div class="sectionbody"> |
| <div class="paragraph"> |
| <p>Apache Cassandra is a distributed database that stores data across a |
| cluster of nodes. A partition key is used to partition data among the |
| nodes. Cassandra partitions data over the storage nodes using a variant |
| of consistent hashing for data distribution. Hashing is a technique used |
| to map data with which given a key, a hash function generates a hash |
| value (or simply a hash) that is stored in a hash table. A partition key |
| is generated from the first field of a primary key. Data partitioned |
| into hash tables using partition keys provides for rapid lookup. Fewer |
| the partitions used for a query faster is the response time for the |
| query.</p> |
| </div> |
| <div class="paragraph"> |
| <p>As an example of partitioning, consider table <code>t</code> in which <code>id</code> is the |
| only field in the primary key.</p> |
| </div> |
| <div class="literalblock"> |
| <div class="content"> |
| <pre>CREATE TABLE t ( |
| id int, |
| k int, |
| v text, |
| PRIMARY KEY (id) |
| );</pre> |
| </div> |
| </div> |
| <div class="paragraph"> |
| <p>The partition key is generated from the primary key <code>id</code> for data |
| distribution across the nodes in a cluster.</p> |
| </div> |
| <div class="paragraph"> |
| <p>Consider a variation of table <code>t</code> that has two fields constituting the |
| primary key to make a composite or compound primary key.</p> |
| </div> |
| <div class="literalblock"> |
| <div class="content"> |
| <pre>CREATE TABLE t ( |
| id int, |
| c text, |
| k int, |
| v text, |
| PRIMARY KEY (id,c) |
| );</pre> |
| </div> |
| </div> |
| <div class="paragraph"> |
| <p>For the table <code>t</code> with a composite primary key the first field <code>id</code> is |
| used to generate the partition key and the second field <code>c</code> is the |
| clustering key used for sorting within a partition. Using clustering |
| keys to sort data makes retrieval of adjacent data more efficient.</p> |
| </div> |
| <div class="paragraph"> |
| <p>In general, the first field or component of a primary key is hashed to |
| generate the partition key and the remaining fields or components are |
| the clustering keys that are used to sort data within a partition. |
| Partitioning data improves the efficiency of reads and writes. The other |
| fields that are not primary key fields may be indexed separately to |
| further improve query performance.</p> |
| </div> |
| <div class="paragraph"> |
| <p>The partition key could be generated from multiple fields if they are |
| grouped as the first component of a primary key. As another variation of |
| the table <code>t</code>, consider a table with the first component of the primary |
| key made of two fields grouped using parentheses.</p> |
| </div> |
| <div class="literalblock"> |
| <div class="content"> |
| <pre>CREATE TABLE t ( |
| id1 int, |
| id2 int, |
| c1 text, |
| c2 text |
| k int, |
| v text, |
| PRIMARY KEY ((id1,id2),c1,c2) |
| );</pre> |
| </div> |
| </div> |
| <div class="paragraph"> |
| <p>For the preceding table <code>t</code> the first component of the primary key |
| constituting fields <code>id1</code> and <code>id2</code> is used to generate the partition |
| key and the rest of the fields <code>c1</code> and <code>c2</code> are the clustering keys |
| used for sorting within a partition.</p> |
| </div> |
| </div> |
| </div> |
| <div class="sect1"> |
| <h2 id="comparing-with-relational-data-model"><a class="anchor" href="#comparing-with-relational-data-model"></a>Comparing with Relational Data Model</h2> |
| <div class="sectionbody"> |
| <div class="paragraph"> |
| <p>Relational databases store data in tables that have relations with other |
| tables using foreign keys. A relational database’s approach to data |
| modeling is table-centric. Queries must use table joins to get data from |
| multiple tables that have a relation between them. Apache Cassandra does |
| not have the concept of foreign keys or relational integrity. Apache |
| Cassandra’s data model is based around designing efficient queries; |
| queries that don’t involve multiple tables. Relational databases |
| normalize data to avoid duplication. Apache Cassandra in contrast |
| de-normalizes data by duplicating data in multiple tables for a |
| query-centric data model. If a Cassandra data model cannot fully |
| integrate the complexity of relationships between the different entities |
| for a particular query, client-side joins in application code may be |
| used.</p> |
| </div> |
| </div> |
| </div> |
| <div class="sect1"> |
| <h2 id="examples-of-data-modeling"><a class="anchor" href="#examples-of-data-modeling"></a>Examples of Data Modeling</h2> |
| <div class="sectionbody"> |
| <div class="paragraph"> |
| <p>As an example, a <code>magazine</code> data set consists of data for magazines with |
| attributes such as magazine id, magazine name, publication frequency, |
| publication date, and publisher. A basic query (Q1) for magazine data is |
| to list all the magazine names including their publication frequency. As |
| not all data attributes are needed for Q1 the data model would only |
| consist of <code>id</code> ( for partition key), magazine name and publication |
| frequency as shown in Figure 1.</p> |
| </div> |
| <div class="imageblock"> |
| <div class="content"> |
| <img src="../_images/Figure_1_data_model.jpg" alt="image"> |
| </div> |
| </div> |
| <div class="paragraph"> |
| <p>Figure 1. Data Model for Q1</p> |
| </div> |
| <div class="paragraph"> |
| <p>Another query (Q2) is to list all the magazine names by publisher. For |
| Q2 the data model would consist of an additional attribute <code>publisher</code> |
| for the partition key. The <code>id</code> would become the clustering key for |
| sorting within a partition. Data model for Q2 is illustrated in Figure |
| 2.</p> |
| </div> |
| <div class="imageblock"> |
| <div class="content"> |
| <img src="../_images/Figure_2_data_model.jpg" alt="image"> |
| </div> |
| </div> |
| <div class="paragraph"> |
| <p>Figure 2. Data Model for Q2</p> |
| </div> |
| </div> |
| </div> |
| <div class="sect1"> |
| <h2 id="designing-schema"><a class="anchor" href="#designing-schema"></a>Designing Schema</h2> |
| <div class="sectionbody"> |
| <div class="paragraph"> |
| <p>After the conceptual data model has been created a schema may be |
| designed for a query. For Q1 the following schema may be used.</p> |
| </div> |
| <div class="literalblock"> |
| <div class="content"> |
| <pre>CREATE TABLE magazine_name (id int PRIMARY KEY, name text, publicationFrequency text)</pre> |
| </div> |
| </div> |
| <div class="paragraph"> |
| <p>For Q2 the schema definition would include a clustering key for sorting.</p> |
| </div> |
| <div class="literalblock"> |
| <div class="content"> |
| <pre>CREATE TABLE magazine_publisher (publisher text,id int,name text, publicationFrequency text, |
| PRIMARY KEY (publisher, id)) WITH CLUSTERING ORDER BY (id DESC)</pre> |
| </div> |
| </div> |
| </div> |
| </div> |
| <div class="sect1"> |
| <h2 id="data-model-analysis"><a class="anchor" href="#data-model-analysis"></a>Data Model Analysis</h2> |
| <div class="sectionbody"> |
| <div class="paragraph"> |
| <p>The data model is a conceptual model that must be analyzed and optimized |
| based on storage, capacity, redundancy and consistency. A data model may |
| need to be modified as a result of the analysis. Considerations or |
| limitations that are used in data model analysis include:</p> |
| </div> |
| <div class="ulist"> |
| <ul> |
| <li> |
| <p>Partition Size</p> |
| </li> |
| <li> |
| <p>Data Redundancy</p> |
| </li> |
| <li> |
| <p>Disk space</p> |
| </li> |
| <li> |
| <p>Lightweight Transactions (LWT)</p> |
| </li> |
| </ul> |
| </div> |
| <div class="paragraph"> |
| <p>The two measures of partition size are the number of values in a |
| partition and partition size on disk. Though requirements for these |
| measures may vary based on the application a general guideline is to |
| keep number of values per partition to below 100,000 and disk space per |
| partition to below 100MB.</p> |
| </div> |
| <div class="paragraph"> |
| <p>Data redundancies as duplicate data in tables and multiple partition |
| replicates are to be expected in the design of a data model , but |
| nevertheless should be kept in consideration as a parameter to keep to |
| the minimum. LWT transactions (compare-and-set, conditional update) |
| could affect performance and queries using LWT should be kept to the |
| minimum.</p> |
| </div> |
| </div> |
| </div> |
| <div class="sect1"> |
| <h2 id="using-materialized-views"><a class="anchor" href="#using-materialized-views"></a>Using Materialized Views</h2> |
| <div class="sectionbody"> |
| <div class="admonitionblock warning"> |
| <table> |
| <tr> |
| <td class="icon"> |
| <i class="fa icon-warning" title="Warning"></i> |
| </td> |
| <td class="content"> |
| <div class="title">Warning</div> |
| <div class="paragraph"> |
| <p>Materialized views (MVs) are experimental in the latest (4.0) release.</p> |
| </div> |
| </td> |
| </tr> |
| </table> |
| </div> |
| <div class="paragraph"> |
| <p>Materialized views (MVs) could be used to implement multiple queries |
| for a single table. A materialized view is a table built from data from |
| another table, the base table, with new primary key and new properties. |
| Changes to the base table data automatically add and update data in a |
| MV. Different queries may be implemented using a materialized view as an |
| MV’s primary key differs from the base table. Queries are optimized by |
| the primary key definition.</p> |
| </div> |
| </div> |
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