|By Srinivasan Sundara Rajan||
|March 14, 2013 11:15 AM EDT||
Data Warehouse as a Service
Recently Amazon announced the availability of Redshift Data warehouse as a Service as a beta offering. Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your existing business intelligence tools. It's optimized for datasets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
Architecture Behind Redshift
Any data warehouse service meant to serve data of petabyte scale should have a robust architecture as its backbone. The following are the salient features of Redshift service.
- Shared Nothing Architecture: As indicated in one of my earlier articles, Cloud Database Scale Out Using Shared Nothing Architecture, the shared nothing architectural pattern is the most desired for databases of this scale and the same concept is adhered to in Redshift. The core component of Redshift is a cluster and each cluster consists of multiple compute nodes, each node has its dedicated storage following the shared nothing principle.
- Massively Parallel Processing (MPP): Hand in hand with the shared nothing pattern MPP provides horizontal scale out capabilities for large data warehouses rather than scaling up the individual servers. Massively parallel processing (MPP) enables fast execution of the most complex queries operating on large amounts of data. Multiple compute nodes handle all query processing leading up to the final result aggregation, with each core of each node executing the same compiled query segments on portions of the entire data. With the concept of NodeSlices Redshift has taken the MPP to the next level to the cores of a compute node. A compute node is partitioned into slices; one slice for each core of the node's multi-core processor. Each slice is allocated a portion of the node's memory and disk space, where it processes a portion of the workload assigned to the node.
Refer to the following diagram from AWS Documentation, about Data warehouse system architecture
- Columnar Data Storage: Storing database table information in a columnar fashion reduces the number of disk I/O requests and reduces the amount of data you need to load from disk. Columnar storage for database tables drastically reduces the overall disk I/O requirements and is an important factor in optimizing analytic query performance.
- Leader Node: The leader node manages most communications with client programs and all communication with compute nodes. It parses and develops execution plans to carry out database operations, in particular, the series of steps necessary to obtain results for complex queries. Based on the execution plan, the leader node distributes compiled code to the compute nodes and assigns a portion of the data to each compute node.
- High Speed Network Connect: The clusters are connected internally by a 10 Gigabit Ethernet network, providing very fast communication between the leader node and the compute clusters.
Best Practices in Application Design on Redshift
The enablement of Big Data analytics through Redshift has created lot of excitement among the community. The usage of these kinds of alternate approaches to traditional data warehousing will be best in conjunction with the best practices for utilizing the features. The following are some of the best practices that can be considered for the design of applications on Redshift.
1. Collocated Tables: It is good practice to try to avoid sending data between the nodes to satisfy JOIN queries. Colocation between two joined tables occurs when the matching rows of the two tables are stored in the same compute nodes, so that the data need not be sent between nodes.
When you add data to a table, Amazon Redshift distributes the rows in the table to the cluster slices using one of two methods:
- Even distribution
- Key distribution
Even distribution is the default distribution method. With even distribution, the leader node spreads data rows across the slices in a round-robin fashion, regardless of the values that exist in any particular column. This approach is a good choice when you don't have a clear option for a distribution key.
If you specify a distribution key when you create a table, the leader node distributes the data rows to the slices based on the values in the distribution key column. Matching values from the distribution key column are stored together.
Colocation is best achieved by choosing the appropriate distribution keys than using the even distribution.
If you frequently join a table, specify the join column as the distribution key. If a table joins with multiple other tables, distribute on the foreign key of the largest dimension that the table joins with. If the dimension tables are filtered as part of the joins, compare the size of the data after filtering when you choose the largest dimension. This ensures that the rows involved with your largest joins will generally be distributed to the same physical nodes. Because local joins avoid data movement, they will perform better than network joins.
2. De-Normalization: In the traditional RDBMS, database storage is optimized by applying the normalization principles such that a particular attribute (column) is associated with one and only entity (Table). However in shared nothing scalable databases like Redshift this technique will not yield the desired results, rather keeping the redundancy of certain columns in the form of de-normalization is very important.
For example, the following query is one of the examples of a high performance query in the Redshift documentation.
SELECT * FROM tab1, tab2
WHERE tab1.key = tab2.key
AND tab1.timestamp > ‘1/1/2013'
AND tab2.timestamp > ‘1/1/2013';
Even if a predicate is already being applied on a table in a join query but transitively applies to another table in the query, it's useful to re-specify the redundant predicate if that other table is also sorted on the column in the predicate. That way, when scanning the other table, Redshift can efficiently skip blocks from that table as well.
By carefully applying de-normalization to bring the required redundancy, Amazon Redshift can perform at its best.
3. Native Parallelism: One of the biggest advantages of a shared nothing MPP architecture is about parallelism. Parallelism is achieved in multiple ways.
- Inter Node Parallelism: It refers the ability of the database system to break up a query into multiple parts across multiple instances across the cluster.
- Intra Node Parallelism: Intra node parallelism refers to the ability to break up query into multiple parts within a single compute node.
Typically in MPP architectures, both Inter Node Parallelism and Intra Node Parallelism will be combined and used at the same time to provide dramatic performance gains.
Amazon Redshift provides lot of operations to utilize both Intra Node and Inter Node parallelism.
When you use a COPY command to load data from Amazon S3, first split your data into multiple files instead of loading all the data from a single large file.
The COPY command then loads the data in parallel from multiple files, dividing the workload among the nodes in your cluster. Split your data into files so that the number of files is a multiple of the number of slices in your cluster. That way Amazon Redshift can divide the data evenly among the slices. Name each file with a common prefix. For example, each XL compute node has two slices, and each 8XL compute node has 16 slices. If you have a cluster with two XL nodes, you might split your data into four files named customer_1, customer_2, customer_3, and customer_4. Amazon Redshift does not take file size into account when dividing the workload, so make sure the files are roughly the same size.
Pre-Processing Data: Over the years RDBMS engines take pride of Location Independence. The Codd's 12 rules of the RDBMS states the following:
Rule 8: Physical data independence:
Changes to the physical level (how the data is stored, whether in arrays or linked lists, etc.) must not require a change to an application based on the structure.
However, in the columnar database services like Redshift the physical ordering of data does make major impact to the performance.
Sorting data is a mechanism for optimizing query performance.
When you create a table, you can define one or more of its columns as the sort key. When data is loaded into the table, the values in the sort key column (or columns) are stored on disk in sorted order. Information about sort key columns is passed to the query planner, and the planner uses this information to construct plans that exploit the way that the data is sorted. For example, a merge join, which is often faster than a hash join, is feasible when the data is distributed and presorted on the joining columns.
The VACUUM command also makes sure that new data in tables is fully sorted on disk. Vacuum as often as you need to in order to maintain a consistent query performance.
Platform as a Service (PaaS) is one of the greatest benefits to the IT community due to the Cloud Delivery Model, and from the beginning of pure play programming models like Windows Azure and Elastic Beanstalk it has moved to high-end services like data warehouse Platform as a Service. As the industry analysts see good adoption of the above service due to the huge cost advantages when compared to the traditional data warehouse platform, the best practices mentioned above will help to achieve the desired level of performance. Detailed documentation is also available on the vendor site in the form of developer and administrator guides.
In his keynote at 19th Cloud Expo, Sheng Liang, co-founder and CEO of Rancher Labs, will discuss the technological advances and new business opportunities created by the rapid adoption of containers. With the success of Amazon Web Services (AWS) and various open source technologies used to build private clouds, cloud computing has become an essential component of IT strategy. However, users continue to face challenges in implementing clouds, as older technologies evolve and newer ones like Docke...
Oct. 21, 2016 02:15 PM EDT Reads: 2,196
Just over a week ago I received a long and loud sustained applause for a presentation I delivered at this year’s Cloud Expo in Santa Clara. I was extremely pleased with the turnout and had some very good conversations with many of the attendees. Over the next few days I had many more meaningful conversations and was not only happy with the results but also learned a few new things. Here is everything I learned in those three days distilled into three short points.
Oct. 21, 2016 02:00 PM EDT Reads: 6,778
Without lifecycle traceability and visibility across the tool chain, stakeholders from Planning-to-Ops have limited insight and answers to who, what, when, why and how across the DevOps lifecycle. This impacts the ability to deliver high quality software at the needed velocity to drive positive business outcomes. In his general session at @DevOpsSummit at 19th Cloud Expo, Eric Robertson, General Manager at CollabNet, will discuss how customers are able to achieve a level of transparency that e...
Oct. 21, 2016 02:00 PM EDT Reads: 565
The reason I believe digital transformation is not only more than a fad, but is actually a life-or-death imperative for every business and IT executive on the planet is simple: there will be no place for an “industrial enterprise” in a digital world. Transformation, by definition, is a metamorphosis from one state to another, wholly new state. As such, a true digital transformation must be the act of transforming an industrial-era organization into something wholly different – the Digital Enter...
Oct. 21, 2016 02:00 PM EDT Reads: 1,218
In his session at 19th Cloud Expo, Claude Remillard, Principal Program Manager in Developer Division at Microsoft, will contrast how his team used config as code and immutable patterns for continuous delivery of microservices and apps to the cloud. He will show the immutable patterns helps developers do away with most of the complexity of config as code-enabling scenarios such as rollback, zero downtime upgrades with far greater simplicity. He will also have live demos of building immutable pipe...
Oct. 21, 2016 01:30 PM EDT Reads: 1,461
Application transformation and DevOps practices are two sides of the same coin. Enterprises that want to capture value faster, need to deliver value faster – time value of money principle. To do that enterprises need to build cloud-native apps as microservices by empowering teams to build, ship, and run in production. In his session at @DevOpsSummit at 19th Cloud Expo, Neil Gehani, senior product manager at HPE, will discuss what every business should plan for how to structure their teams to d...
Oct. 21, 2016 01:00 PM EDT Reads: 1,221
When we talk about the impact of BYOD and BYOA and the Internet of Things, we often focus on the impact on data center architectures. That's because there will be an increasing need for authentication, for access control, for security, for application delivery as the number of potential endpoints (clients, devices, things) increases. That means scale in the data center. What we gloss over, what we skip, is that before any of these "things" ever makes a request to access an application it had to...
Oct. 21, 2016 11:45 AM EDT Reads: 13,560
SYS-CON Events announced today that Transparent Cloud Computing (T-Cloud) Consortium will exhibit at the 19th International Cloud Expo®, which will take place on November 1–3, 2016, at the Santa Clara Convention Center in Santa Clara, CA. The Transparent Cloud Computing Consortium (T-Cloud Consortium) will conduct research activities into changes in the computing model as a result of collaboration between "device" and "cloud" and the creation of new value and markets through organic data proces...
Oct. 21, 2016 10:30 AM EDT Reads: 1,232
Oct. 21, 2016 10:00 AM EDT Reads: 3,706
In many organizations governance is still practiced by phase or stage gate peer review, and Agile projects are forced to accommodate, which leads to WaterScrumFall or worse. But governance criteria and policies are often very weak anyway, out of date or non-existent. Consequently governance is frequently a matter of opinion and experience, highly dependent upon the experience of individual reviewers. As we all know, a basic principle of Agile methods is delegation of responsibility, and ideally ...
Oct. 21, 2016 10:00 AM EDT Reads: 3,009
Today every business relies on software to drive the innovation necessary for a competitive edge in the Application Economy. This is why collaboration between development and operations, or DevOps, has become IT’s number one priority. Whether you are in Dev or Ops, understanding how to implement a DevOps strategy can deliver faster development cycles, improved software quality, reduced deployment times and overall better experiences for your customers.
Oct. 21, 2016 09:30 AM EDT Reads: 442
Apache Hadoop is a key technology for gaining business insights from your Big Data, but the penetration into enterprises is shockingly low. In fact, Apache Hadoop and Big Data proponents recognize that this technology has not yet achieved its game-changing business potential. In his session at 19th Cloud Expo, John Mertic, director of program management for ODPi at The Linux Foundation, will explain why this is, how we can work together as an open data community to increase adoption, and the i...
Oct. 21, 2016 08:15 AM EDT Reads: 1,837
All clouds are not equal. To succeed in a DevOps context, organizations should plan to develop/deploy apps across a choice of on-premise and public clouds simultaneously depending on the business needs. This is where the concept of the Lean Cloud comes in - resting on the idea that you often need to relocate your app modules over their life cycles for both innovation and operational efficiency in the cloud. In his session at @DevOpsSummit at19th Cloud Expo, Valentin (Val) Bercovici, CTO of So...
Oct. 21, 2016 07:45 AM EDT Reads: 2,058
JetBlue Airways uses virtual environments to reduce software development costs, centralize performance testing, and create a climate for continuous integration and real-time monitoring of mobile applications. The next BriefingsDirect Voice of the Customer performance engineering case study discussion examines how JetBlue Airways in New York uses virtual environments to reduce software development costs, centralize performance testing, and create a climate for continuous integration and real-tim...
Oct. 21, 2016 07:45 AM EDT Reads: 1,172
Virgil consists of an open-source encryption library, which implements Cryptographic Message Syntax (CMS) and Elliptic Curve Integrated Encryption Scheme (ECIES) (including RSA schema), a Key Management API, and a cloud-based Key Management Service (Virgil Keys). The Virgil Keys Service consists of a public key service and a private key escrow service.
Oct. 21, 2016 07:15 AM EDT Reads: 891
SYS-CON Events announced today that eCube Systems, the leading provider of modern development tools and best practices for Continuous Integration on OpenVMS, will exhibit at SYS-CON's @DevOpsSummit at Cloud Expo New York, which will take place on June 7-9, 2016, at the Javits Center in New York City, NY. eCube Systems offers a family of middleware products and development tools that maximize return on technology investment by leveraging existing technical equity to meet evolving business needs. ...
Oct. 21, 2016 07:00 AM EDT Reads: 4,403
Let's just nip the conflation of these terms in the bud, shall we?
"MIcro" is big these days. Both microservices and microsegmentation are having and will continue to have an impact on data center architecture, but not necessarily for the same reasons. There's a growing trend in which folks - particularly those with a network background - conflate the two and use them to mean the same thing.
They are not.
One is about the application. The other, the network. T...
Oct. 21, 2016 06:45 AM EDT Reads: 6,317
This is a no-hype, pragmatic post about why I think you should consider architecting your next project the way SOA and/or microservices suggest. No matter if it’s a greenfield approach or if you’re in dire need of refactoring. Please note: considering still keeps open the option of not taking that approach. After reading this, you will have a better idea about whether building multiple small components instead of a single, large component makes sense for your project. This post assumes that you...
Oct. 21, 2016 06:00 AM EDT Reads: 7,157
DevOps is speeding towards the IT world like a freight train and the hype around it is deafening. There is no reason to be afraid of this change as it is the natural reaction to the agile movement that revolutionized development just a few years ago. By definition, DevOps is the natural alignment of IT performance to business profitability. The relevance of this has yet to be quantified but it has been suggested that the route to the CEO’s chair will come from the IT leaders that successfully ma...
Oct. 21, 2016 04:30 AM EDT Reads: 16,211
@DevOpsSummit has been named the ‘Top DevOps Influencer' by iTrend. iTrend processes millions of conversations, tweets, interactions, news articles, press releases, blog posts - and extract meaning form them and analyzes mobile and desktop software platforms used to communicate, various metadata (such as geo location), and automation tools. In overall placement, @DevOpsSummit ranked as the number one ‘DevOps Influencer' followed by @CloudExpo at third, and @MicroservicesE at 24th.
Oct. 21, 2016 03:30 AM EDT Reads: 3,776