DISTRIBUTION KEY REDSHIFT HOW TO
DISTRIBUTION KEY REDSHIFT FULL

Uses a column that is frequently used to join different large tables (by means of a join).And the crown jewel is distribution style KEY, recommended for fact tables of high volume and which allows the user to define which column acts as the distribution key.Ī good distribution key is usually chosen so that it meets, in part or in full, the following conditions: This is useful when there is no clear distribution key. Another distribution style is EVEN, defined by default, which distributes the table among all nodes in a round-robin mode, that is, in equal chunks. One of these is ALL, which distributes a copy of the table in all nodes, and as we said it is recommended for widely used tables with very few records (such as dimension or look up tables). And with this in mind, what kind of distribution styles does Amazon Redshift offer? Only three.

DISTRIBUTION KEY REDSHIFT FULL

There are two common problems associated with this movement: a performance problem, as a large amount of data has to be moved and a full disk issue, as the query exceeds the storage capacity of the node.ĭue to these characteristics, it is very important to define a dist key that distributes the data in the most efficient way. Later, when performing a query, the planner defines which data blocks have to be moved between nodes to generate the result. When a table is loaded into Amazon Redshift, it is distributed among nodes based on the distribution style. The first three concepts revolve around the way Amazon Redshift stores data, while the last deals with the way Amazon Redshift queries the data.

Constraints: Allows you to tell the Amazon Redshift planner the features of your model to improve your consultation plans.

DISTRIBUTION KEY REDSHIFT HOW TO

Column compression: This tells Amazon Redshift how to compress columns, resulting in better use of space.Sorting keys (sort key): These allow you to tell Amazon Redshift how you sort your data, making sorting more efficient.Distribution keys (dist key): these allow you to tell Amazon Redshift how your data is grouped so that distribution between nodes is more effective.In this section we will discuss the main parameter keys to get the most out of our data warehouse at Amazon Redshift: In addition, we need to change the way we view data collection, although that will be discussed in more detail in the next section. Nonetheless, it is very important to define certain parameters in Amazon Redshift. In general, as a relational database, modeling is conceptually similar to other more traditional databases. To take full advantage of the benefits offered by Amazon Redshift as a distributed columnar database, it is very important to define the data model correctly. This allows our Redshift cluster to be scaled according to our needs, always keeping the focus on the size of the dataset and the desired query speed.

Clusters with “ large” type nodes consist of between 1 and 32 nodes, while “ 8xlarge” nodes consist of a minimum of 2 nodes up to 128. In both types of nodes we can choose two varieties: “(x)large” and “8xlarge”. Their use of solid state drive (SSD) storage offers faster I/O (input/output) than DS2 nodes, but they provide less storage space, as each node has a capacity of 160GB. The other DC2 node types are optimized for high performance workloads. Each node has a capacity of 2TB of storage, which allows for great storage in a local cluster using nodes of this type. The DS2 node types are optimized for large data workloads and use Hard Disk Drive (HDD) storage. Types of nodes offered by AWSĪs shown in the previous diagram, Amazon Redshift offers two types of nodes, one oriented to higher computing capacity ( DC2) and another oriented to storage ( DS2). SSD scales from 160GB to 256TB.ĭS: Dense Storage. Partitioned areas of the node’s memory and disk space where the allocated load is processed.ĭC: Dense Compute. Amazon Redshift is the Amazon Web Services (AWS) service offering a fast, fully managed, secure and scalable data warehouse.īuilt on massive parallel processing (MPP) technology, it allows for large-scale dataset processing and database migrations.Īmazon Redshift differs from other databases in that it can process analytical workloads on large datasets, stored via column-oriented database management (DBMS).

Distribution key redshift