|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.
There is an ever-growing explosion of new devices that are connected to the Internet using “cloud” solutions. This rapid growth is creating a massive new demand for efficient access to data. And it’s not just about connecting to that data anymore. This new demand is bringing new issues and challenges and it is important for companies to scale for the coming growth. And with that scaling comes the need for greater security, gathering and data analysis, storage, connectivity and, of course, the...
May. 4, 2016 03:30 AM EDT Reads: 1,131
The IoTs will challenge the status quo of how IT and development organizations operate. Or will it? Certainly the fog layer of IoT requires special insights about data ontology, security and transactional integrity. But the developmental challenges are the same: People, Process and Platform. In his session at @ThingsExpo, Craig Sproule, CEO of Metavine, will demonstrate how to move beyond today's coding paradigm and share the must-have mindsets for removing complexity from the development proc...
May. 4, 2016 03:00 AM EDT Reads: 777
Redis is not only the fastest database, but it has become the most popular among the new wave of applications running in containers. Redis speeds up just about every data interaction between your users or operational systems. In his session at 18th Cloud Expo, Dave Nielsen, Developer Relations at Redis Labs, will shares the functions and data structures used to solve everyday use cases that are driving Redis' popularity.
May. 4, 2016 12:45 AM EDT Reads: 1,180
Much of the value of DevOps comes from a (renewed) focus on measurement, sharing, and continuous feedback loops. In increasingly complex DevOps workflows and environments, and especially in larger, regulated, or more crystallized organizations, these core concepts become even more critical. In his session at @DevOpsSummit at 18th Cloud Expo, Andi Mann, Chief Technology Advocate at Splunk, will show how, by focusing on 'metrics that matter,' you can provide objective, transparent, and meaningfu...
May. 3, 2016 11:45 PM EDT Reads: 1,010
Many private cloud projects were built to deliver self-service access to development and test resources. While those clouds delivered faster access to resources, they lacked visibility, control and security needed for production deployments. In their session at 18th Cloud Expo, Steve Anderson, Product Manager at BMC Software, and Rick Lefort, Principal Technical Marketing Consultant at BMC Software, will discuss how a cloud designed for production operations not only helps accelerate developer...
May. 3, 2016 11:30 PM EDT Reads: 1,237
Artificial Intelligence has the potential to massively disrupt IoT. In his session at 18th Cloud Expo, AJ Abdallat, CEO of Beyond AI, will discuss what the five main drivers are in Artificial Intelligence that could shape the future of the Internet of Things. AJ Abdallat is CEO of Beyond AI. He has over 20 years of management experience in the fields of artificial intelligence, sensors, instruments, devices and software for telecommunications, life sciences, environmental monitoring, process...
May. 3, 2016 11:00 PM EDT Reads: 1,210
Increasing IoT connectivity is forcing enterprises to find elegant solutions to organize and visualize all incoming data from these connected devices with re-configurable dashboard widgets to effectively allow rapid decision-making for everything from immediate actions in tactical situations to strategic analysis and reporting. In his session at 18th Cloud Expo, Shikhir Singh, Senior Developer Relations Manager at Sencha, will discuss how to create HTML5 dashboards that interact with IoT devic...
May. 3, 2016 10:00 PM EDT Reads: 1,324
SYS-CON Events announced today that Ericsson has been named “Gold Sponsor” of SYS-CON's @ThingsExpo, which will take place on June 7-9, 2016, at the Javits Center in New York, New York. Ericsson is a world leader in the rapidly changing environment of communications technology – providing equipment, software and services to enable transformation through mobility. Some 40 percent of global mobile traffic runs through networks we have supplied. More than 1 billion subscribers around the world re...
May. 3, 2016 08:45 PM EDT Reads: 1,284
In the world of DevOps there are ‘known good practices’ – aka ‘patterns’ – and ‘known bad practices’ – aka ‘anti-patterns.' Many of these patterns and anti-patterns have been developed from real world experience, especially by the early adopters of DevOps theory; but many are more feasible in theory than in practice, especially for more recent entrants to the DevOps scene. In this power panel at @DevOpsSummit at 18th Cloud Expo, moderated by DevOps Conference Chair Andi Mann, panelists will dis...
May. 3, 2016 08:45 PM EDT Reads: 972
Struggling to keep up with increasing application demand? Learn how Platform as a Service (PaaS) can streamline application development processes and make resource management easy.
May. 3, 2016 08:45 PM EDT Reads: 2,200
The increasing popularity of the Internet of Things necessitates that our physical and cognitive relationship with wearable technology will change rapidly in the near future. This advent means logging has become a thing of the past. Before, it was on us to track our own data, but now that data is automatically available. What does this mean for mHealth and the "connected" body? In her session at @ThingsExpo, Lisa Calkins, CEO and co-founder of Amadeus Consulting, will discuss the impact of wea...
May. 3, 2016 08:00 PM EDT Reads: 1,057
If there is anything we have learned by now, is that every business paves their own unique path for releasing software- every pipeline, implementation and practices are a bit different, and DevOps comes in all shapes and sizes. Software delivery practices are often comprised of set of several complementing (or even competing) methodologies – such as leveraging Agile, DevOps and even a mix of ITIL, to create the combination that’s most suitable for your organization and that maximize your busines...
May. 3, 2016 07:30 PM EDT Reads: 1,920
Up until last year, enterprises that were looking into cloud services usually undertook a long-term pilot with one of the large cloud providers, running test and dev workloads in the cloud. With cloud’s transition to mainstream adoption in 2015, and with enterprises migrating more and more workloads into the cloud and in between public and private environments, the single-provider approach must be revisited. In his session at 18th Cloud Expo, Yoav Mor, multi-cloud solution evangelist at Cloudy...
May. 3, 2016 06:30 PM EDT Reads: 1,654
In his session at 18th Cloud Expo, Sagi Brody, Chief Technology Officer at Webair Internet Development Inc., will focus on real world deployments of DDoS mitigation strategies in every layer of the network. He will give an overview of methods to prevent these attacks and best practices on how to provide protection in complex cloud platforms. He will also outline what we have found in our experience managing and running thousands of Linux and Unix managed service platforms and what specifically c...
May. 3, 2016 05:45 PM EDT Reads: 1,258
Peak 10, Inc., has announced the implementation of IT service management, a business process alignment initiative based on the widely adopted Information Technology Infrastructure Library (ITIL) framework. The implementation of IT service management enhances Peak 10’s current service-minded approach to IT delivery by propelling the company to deliver higher levels of personalized and prompt service. The majority of Peak 10’s operations employees have been trained and certified in the ITIL frame...
May. 3, 2016 05:15 PM EDT Reads: 1,114
trust and privacy in their ecosystem. Assurance and protection of device identity, secure data encryption and authentication are the key security challenges organizations are trying to address when integrating IoT devices. This holds true for IoT applications in a wide range of industries, for example, healthcare, consumer devices, and manufacturing. In his session at @ThingsExpo, Lancen LaChance, vice president of product management, IoT solutions at GlobalSign, will teach IoT developers how t...
May. 3, 2016 05:00 PM EDT Reads: 339
See storage differently! Storage performance problems have only gotten worse and harder to solve as applications have become largely virtualized and moved to a cloud-based infrastructure. Storage performance in a virtualized environment is not just about IOPS, it is about how well that potential performance is guaranteed to individual VMs for these apps as the number of VMs keep going up real time. In his session at 18th Cloud Expo, Dhiraj Sehgal, in product and marketing at Tintri, will discu...
May. 3, 2016 01:00 PM EDT Reads: 980
Whether your IoT service is connecting cars, homes, appliances, wearable, cameras or other devices, one question hangs in the balance – how do you actually make money from this service? The ability to turn your IoT service into profit requires the ability to create a monetization strategy that is flexible, scalable and working for you in real-time. It must be a transparent, smoothly implemented strategy that all stakeholders – from customers to the board – will be able to understand and comprehe...
May. 3, 2016 12:30 PM EDT Reads: 1,179
You deployed your app with the Bluemix PaaS and it's gaining some serious traction, so it's time to make some tweaks. Did you design your application in a way that it can scale in the cloud? Were you even thinking about the cloud when you built the app? If not, chances are your app is going to break. Check out this webcast to learn various techniques for designing applications that will scale successfully in Bluemix, for the confidence you need to take your apps to the next level and beyond.
May. 3, 2016 12:15 PM EDT Reads: 1,593
SYS-CON Events announced today that Peak 10, Inc., a national IT infrastructure and cloud services provider, will exhibit at SYS-CON's 18th International Cloud Expo®, which will take place on June 7-9, 2016, at the Javits Center in New York City, NY. Peak 10 provides reliable, tailored data center and network services, cloud and managed services. Its solutions are designed to scale and adapt to customers’ changing business needs, enabling them to lower costs, improve performance and focus inter...
May. 3, 2016 12:00 PM EDT Reads: 1,372