Data is a key aspect of any company. It helps in the decision-making process and can predict trends in consumer purchase behavior and other high-level functionalities. What’s more, this information is known to grow with the company’s size. As a firm gets more and more clients and expands, the data size generated keeps increasing. While this is a good thing, it has its complexities as well. Why? Data size directly impacts storage size and costs, something that is the parent company’s sole responsibility. That’s not all. Data size has an impact on query performance.
With this in mind, the less the data, the less complicated expensive disk I/O operations get. However, companies cannot scale down the amount of data generated, can they? What they can do is compress the generated data using Amazon Redshift Compression.
In this article, you will get acquainted with Amazon Redshift Compression. More specifically, you will understand the types of amazon Redshift Compression Encodings, queries, and the best tips for selecting Amazon Redshift Compression Encoding for your company.
Table of Contents
Introduction to Amazon Redshift
Amazon Redshift is the Cloud Data Warehouse offered by AWS (Amazon Web Services) that helps companies store and analyze their business data using the storage and computing resources of the Amazon Redshift. It delivers high query performance using techniques such as Columnar Data Storage and Massive Parallel Processing (MPP) to generate query responses quickly.
Columnar Data Storage distributes the data in columns rather than in rows to reduce the storage space. Also, the Massive Parallel Processing technique distributes the workload across multiple nodes in a cluster. It significantly improves the query response time. Amazon Redshift is capable of handling data on an exabytes scale and data hosted on it is encrypted to provide high-grade security against cyber attacks.
Key Features of Amazon Redshift
Some of the main features of Amazon Redshift are listed below:
- Redshift ML: Amazon Redshift offers pre-built environment leverage with Machine Learning for Data Scientists, Data Analysts, Developers, and Business Professionals to create, test and deploy AWS SageMaker models using standard SQL commands.
- Automated Backups: Amazon Redshift comes with auto backup services to Amazon S3. The data from the primary cluster is back up to multiple Amazon S3 located in different regions to prevent any data loss, server downtime and make data available all the time.
- End-to-End Encryption: Amazon Redshift ensures that the user’s data stay protected and they can manage data access to other users. It secures data with AES-256 Encryption and transfers data over SSL.
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Understanding Amazon Redshift Compression Encodings
Before we get to Amazon Redshift Compression Encodings, we need to define data compression and see what benefits it poses for your stored data.
Amazon Redshift Compression is referred to as Encoding. It is a technique of converting data into a format that occupies less space. The redundant nature of data forms the basis of encoding. For instance, take a situation where your company specializes in selling millions of items. However, you only sell several thousand items to millions of customers in reality.
Hence, each item is repeated thousands of items in your sales tables. This data is highly redundant and ends up consuming lots of space. Amazon Redshift Compression would come in handy in such situations.
In summary, Amazon Redshift Compression offers several Encoding types helpful in reducing data size, saving storage costs, and improving query performance. So, which are these Amazon Redshift Compression Encodings types?
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Amazon Redshift Compression Encoding Types
Now that you have understood about Amazon Redshift Compression Encoding. Depending on the data type, there are several types of Amazon Redshift Compression Encoding as listed below:
This means the data is not compressed. It can apply to all data types depending on your needs. Ideally, columns, defined as sort keys, are assigned RAW compression. Other column data types assigned RAW compression are REAL, DOUBLE PRECISION, and BOOLEAN.
2) LZO- LZO
LZO- LZO Compression is automatically assigned by Amazon Redshift to most data types. This is because it offers a good performance to compression ratio. Some of the data types that work well with this compression are CHAR and VARCHAR and columns of strings.
This encoding is primarily used with numerical data types. In instances where the column is larger than most stored data, this encoding might work. Here, you compress the most values to a smaller standard and keep the large values in their raw form.
4) Run-length Encoding
This encoding works by substituting the repetitive values with tokens pointing to the actual values. Therefore, you can use it to compress columnar data that takes values from a relatively small dictionary of partially ordered values.
5) Text255 and Text32K Encodings
These encodings check for repetitive terms inside the text in columnar data. Therefore, if you identify a column with strings that contain specific terms, you can implement these encoding techniques.
This generic encoding can be used with all data types in Amazon Redshift but works best with CHAR and VARCHAR columns. If none of the listed data types applies to your columnar data, you can implement ZStandard.
Benefits of Amazon Redshift Compression Encoding
With all this information, you might be wondering just why you should utilize Amazon Redshift Compression Encoding. Well, there are several compelling reasons that prove the usefulness of this process.
- Reduction in Costs: By performing Amazon Redshift Data Encoding, you reduce the space occupied by your data without affecting the nature of your information. This basically implies that your data will not change, it will merely occupy less space.
- Improves Performance: Amazon Redshift Compression Encoding improves overall query performance by reducing the I/O needed to process SQL requests.
Above are some of the compelling reasons why you need Amazon Redshift Compression Encoding. The most significant one is a reduction in storage costs. This is because by reducing the amount of space occupied by data, you can free up more storage to occupy even more information which is a huge benefit for your business.
With all this information in mind, one question still hasn’t been answered sufficiently: how do you choose the best type of encoding? Read on to find out.
Best Tips for Selecting the Amazon Redshift Compression Encodings
From the information above, the type of Amazon Redshift Compression Encoding that will work best will depend on your data and what you intend to get out of it. Luckily, you do not need to understand all the different algorithms to select the best one for your data.
Amazon takes care of this for you. The platform has a very useful tool you can implement to check for the best encoding for your data. You have to load your data into a test table and execute the following command in the SQL console.
ANALYZE COMPRESSION test_table;
The output will inform you of the recommended Amazon Redshift Compression Encoding for each column, a factor that will be highly dependent on the data you have loaded. It is recommended to use at least 100 000 rows of data.
In this article, you learnt about some of the Amazon Redshift Compression Encoding Types, how they work, why they are useful for queries, and some of the best tips to use Amazon Redshift Compression Encodings. By now, you should have a rough idea of what Amazon Redshift Compression Encoding goes with each data type. With this information at hand, you stand at a better chance of managing your Amazon Redshift data and getting the most out of your queries.
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