Welcome!

AJAX & REA Authors: Alfredo Diaz, Andreas Grabner, Tim Hinds, RealWire News Distribution

Related Topics: Apache, Java, Open Source, AJAX & REA, Cloud Expo

Apache: Blog Feed Post

GridGain and Hadoop: Differences and Synergies

Now data can be analyzed and processed at any point of its lifecycle

GridGain is Java-based middleware for in-memory processing of big data in a distributed environment. It is based on high performance in-memory data platform that integrates fast In-Memory MapReduce implementation with In-Memory Data Grid technology delivering easy to use and easy to scale software. Using GridGain you can process terabytes of data, on 1000s of nodes in under a second.

GridGain typically resides between business, analytics, transactional or BI applications and long term data storage such as RDBMS, ERP or Hadoop HDFS, and provides in-memory data platform for high performance, low latency data storage and processing.

Both, GridGain and Hadoop, are designed for parallel processing of distributed data. However, both products serve very different goals and in most cases are very complementary to each other. Hadoop is mostly geared towards batch-oriented offline processing of historical and analytics payloads where latencies and transactions don’t really matter, while GridGain is meant for real-time in-memory processing of both transactional and non-transactional live data with very low latencies. To better understand where each product really fits, let us compare some main concepts of each product.

GridGain In-Memory Compute Grid vs Hadoop MapReduce
MapReduce
is a programming model developed by Google for processing large data sets of data stored on disks. Hadoop MapReduce is an implementation of such model. The model is based on the fact that data in a single file can be distributed across multiple nodes and hence the processing of those files has to be co-located on the same nodes to avoid moving data around. The processing is based on scanning files record by record in parallel on multiple nodes and then reducing the results in parallel on multiple nodes as well. Because of that, standard disk-based MapReduce is good for problem sets which require analyzing every single record in a file and does not fit for cases when direct access to a certain data record is required. Furthermore, due to offline batch orientation of Hadoop it is not suited for low-latency applications.

GridGain In-Memory Compute Grid (IMCG) on the other hand is geared towards in-memory computations and very low latencies. GridGain IMCG has its own implementation of MapReduce which is designed specifically for real-time in-memory processing use cases and is very different from Hadoop one. Its main goal is to split a task into multiple sub-tasks, load balance those sub-tasks among available cluster nodes, execute them in parallel, then aggregate the results from those sub-tasks and return them to user.



Splitting tasks into multiple sub-tasks and assigning them to nodes is the *mapping* step and aggregating of results is *reducing* step. However, there is no concept of mandatory data built in into this design and it can work in the absence of any data at all which makes it a good fit for both, stateless and state-full computations, like traditional HPC. In cases when data is present, GridGain IMCG will also automatically colocate computations with the nodes where the data is to avoid redundant data movement.

It is also worth mentioning, that unlike Hadoop, GridGain IMCG is very well suited for processing of computations which are very short-lived in nature, e.g. below 100 milliseconds and may not require any mapping or reducing.

Here is a simple Java coding example of GridGain IMCG which counts number of letters in a phrase by splitting it into multiple words, assigning each word to a sub-task for parallel remote execution in the map step, and then adding all lengths receives from remote jobs in reduce step.

    int letterCount = g.reduce(
        BALANCE,
        // Mapper
        new GridClosure<String, Integer>() {
            @Override public Integer apply(String s) {
                return s.length();
            }
        },
        Arrays.asList("GridGain Letter Count".split(" ")),
        // Reducer
        F.sumIntReducer()
    ));

GridGain In-Memory Data Grid vs Hadoop Distributed File System
Hadoop Distributed File System (HDFS) is designed for storing large amounts of data in files on disk. Just like any file system, the data is mostly stored in textual or binary formats. To find a single record inside an HDFS file requires a file scan. Also, being distributed in nature, to update a single record within a file in HDFS requires copying of a whole file (file in HDFS can only be appended). This makes HDFS well-suited for cases when data is appended at the end of a file, but not well suited for cases when data needs to be located and/or updated in the middle of a file. With indexing technologies, like HBase or Impala, data access becomes somewhat easier because keys can be indexed, but not being able to index into values (secondary indexes) only allow for primitive query execution.

GridGain In-Memory Data Grid (IMDG) on the other hand is an in-memory key-value data store. The roots of IMDGs came from distributed caching, however GridGain IMDG also adds transactions, data partitioning, and SQL querying to cached data. The main difference with HDFS (or Hadoop ecosystem overall) is the ability to transact and update any data directly in real time. This makes GridGain IMDG well suited for working on operational data sets, the data sets that are currently being updated and queried, while HDFS is suited for working on historical data which is constant and will never change.

Unlike a file system, GridGain IMDG works with user domain model by directly caching user application objects. Objects are accessed and updated by key which allows IMDG to work with volatile data which requires direct key-based access.



GridGain IMDG allows for indexing into keys and values (i.e. primary and secondary indices) and supports native SQL for data querying & processing. One of unique features of GridGain IMDG is support for distributed joins which allow to execute complex SQL queries on the data in-memory without limitations.

GridGain and Hadoop Working Together
To summarize:

Hadoop essentially is a Big Data warehouse which is good for batch processing of historic data that never changes, while GridGain, on the other hand, is an In-Memory Data Platform which works with your current operational data set in transactional fashion with very low latencies. Focusing on very different use cases make GridGain and Hadoop very complementary with each other.



Up-Stream Integration
The diagram above shows integration between GridGain and Hadoop. Here we have GridGain In-Memory Compute Grid and Data Grid working directly in real-time with user application by partitioning and caching data within data grid, and executing in-memory computations and SQL queries on it. Every so often, when data becomes historic, it is snapshotted into HDFS where it can be analyzed using Hadoop MapReduce and analytical tools from Hadoop eco-system.

Down-Stream Integration
Another possible way to integrate would be for cases when data is already stored in HDFS but needs to be loaded into IMDG for faster in-memory processing. For cases like that GridGain provides fast loading mechanisms from HDFS into GridGain IMDG where it can be further analyzed using GridGain in-memory Map Reduce and indexed SQL queries.

Conclusion
Integration between an in-memory data platform like GridGain and disk based data platform like Hadoop allows businesses to get valuable insights into the whole data set at once, including volatile operational data set cached in memory, as well as historic data set stored in Hadoop. This essentially eliminates any gaps in processing time caused by Extract-Transfer-Load (ETL) process of copying data from operational system of records, like standard databases, into historic data warehouses like Hadoop. Now data can be analyzed and processed at any point of its lifecycle, from the moment when it gets into the system up until it gets put away into a warehouse.

Read the original blog entry...

More Stories By Thomas Krafft

Over 15 years of experience in marketing and demand creation, with strategies driving over $500 million in revenue for a variety of companies in several high-growth and competitive markets, including consumer software and web services, ecommerce, demand creation through web and search, big data, and now healthcare.

Cloud Expo Breaking News
Cloud scalability and performance should be at the heart of every successful Internet venture. The infrastructure needs to be resilient, flexible, and fast – it’s best not to get caught thinking about architecture until the middle of an emergency, when it's too late. In his interactive, no-holds-barred session at 14th Cloud Expo, Phil Jackson, Development Community Advocate for SoftLayer, will dive into how to design and build-out the right cloud infrastructure.
Cloud backup and recovery services are critical to safeguarding an organization’s data and ensuring business continuity when technical failures and outages occur. With so many choices, how do you find the right provider for your specific needs? In his session at 14th Cloud Expo, Daniel Jacobson, Technology Manager at BUMI, will outline the key factors including backup configurations, proactive monitoring, data restoration, disaster recovery drills, security, compliance and data center resources. Aside from the technical considerations, the secret sauce in identifying the best vendor is the level of focus, expertise and specialization of their engineering team and support group, and how they monitor your day-to-day backups, provide recommendations, and guide you through restores when necessary.
More and more enterprises today are doing business by opening up their data and applications through APIs. Though forward-thinking and strategic, exposing APIs also increases the surface area for potential attack by hackers. To benefit from APIs while staying secure, enterprises and security architects need to continue to develop a deep understanding about API security and how it differs from traditional web application security or mobile application security. In his session at 14th Cloud Expo, Sachin Agarwal, VP of Product Marketing and Strategy at SOA Software, will walk you through the various aspects of how an API could be potentially exploited. He will discuss the necessary best practices to secure your data and enterprise applications while continue continuing to support your business’s digital initiatives.
The revolution that happened in the server universe over the past 15 years has resulted in an eco-system that is more open, more democratically innovative and produced better results in technically challenging dimensions like scale. The underpinnings of the revolution were common hardware, standards based APIs (ex. POSIX) and a strict adherence to layering and isolation between applications, daemons and kernel drivers/modules which allowed multiple types of development happen in parallel without hindering others. Put simply, today's server model is built on a consistent x86 platform with few surprises in its core components. A kernel abstracts away the platform, so that applications and daemons are decoupled from the hardware. In contrast, networking equipment is still stuck in the mainframe era. Today, networking equipment is a single appliance, including hardware, OS, applications and user interface come as a monolithic entity from a single vendor. Switching between different vendor'...
You use an agile process; your goal is to make your organization more agile. What about your data infrastructure? The truth is, today’s databases are anything but agile – they are effectively static repositories that are cumbersome to work with, difficult to change, and cannot keep pace with application demands. Performance suffers as a result, and it takes far longer than it should to deliver on new features and capabilities needed to make your organization competitive. As your application and business needs change, data repositories and structures get outmoded rapidly, resulting in increased work for application developers and slow performance for end users. Further, as data sizes grow into the Big Data realm, this problem is exacerbated and becomes even more difficult to address. A seemingly simple schema change can take hours (or more) to perform, and as requirements evolve the disconnect between existing data structures and actual needs diverge.
SYS-CON Events announced today that SherWeb, a long-time leading provider of cloud services and Microsoft's 2013 World Hosting Partner of the Year, will exhibit at SYS-CON's 14th International Cloud Expo®, which will take place on June 10–12, 2014, at the Javits Center in New York City, New York. A worldwide hosted services leader ranking in the prestigious North American Deloitte Technology Fast 500TM, and Microsoft's 2013 World Hosting Partner of the Year, SherWeb provides competitive cloud solutions to businesses and partners around the world. Founded in 1998, SherWeb is a privately owned company headquartered in Quebec, Canada. Its service portfolio includes Microsoft Exchange, SharePoint, Lync, Dynamics CRM and more.
The world of cloud and application development is not just for the hardened developer these days. In their session at 14th Cloud Expo, Phil Jackson, Development Community Advocate for SoftLayer, and Harold Hannon, Sr. Software Architect at SoftLayer, will pull back the curtain of the architecture of a fun demo application purpose-built for the cloud. They will focus on demonstrating how they leveraged compute, storage, messaging, and other cloud elements hosted at SoftLayer to lower the effort and difficulty of putting together a useful application. This will be an active demonstration and review of simple command-line tools and resources, so don’t be afraid if you are not a seasoned developer.
SYS-CON Events announced today that BUMI, a premium managed service provider specializing in data backup and recovery, will exhibit at SYS-CON's 14th International Cloud Expo®, which will take place on June 10–12, 2014, at the Javits Center in New York City, New York. Manhattan-based BUMI (Backup My Info!) is a premium managed service provider specializing in data backup and recovery. Founded in 2002, the company’s Here, There and Everywhere data backup and recovery solutions are utilized by more than 500 businesses. BUMI clients include professional service organizations such as banking, financial, insurance, accounting, hedge funds and law firms. The company is known for its relentless passion for customer service and support, and has won numerous awards, including Customer Service Provider of the Year and 10 Best Companies to Work For.
Chief Security Officers (CSO), CIOs and IT Directors are all concerned with providing a secure environment from which their business can innovate and customers can safely consume without the fear of Distributed Denial of Service attacks. To be successful in today's hyper-connected world, the enterprise needs to leverage the capabilities of the web and be ready to innovate without fear of DDoS attacks, concerns about application security and other threats. Organizations face great risk from increasingly frequent and sophisticated attempts to render web properties unavailable, and steal intellectual property or personally identifiable information. Layered security best practices extend security beyond the data center, delivering DDoS protection and maintaining site performance in the face of fast-changing threats.
From data center to cloud to the network. In his session at 3rd SDDC Expo, Raul Martynek, CEO of Net Access, will identify the challenges facing both data center providers and enterprise IT as they relate to cross-platform automation. He will then provide insight into designing, building, securing and managing the technology as an integrated service offering. Topics covered include: High-density data center design Network (and SDN) integration and automation Cloud (and hosting) infrastructure considerations Monitoring and security Management approaches Self-service and automation
In his session at 14th Cloud Expo, David Holmes, Vice President at OutSystems, will demonstrate the immense power that lives at the intersection of mobile apps and cloud application platforms. Attendees will participate in a live demonstration – an enterprise mobile app will be built and changed before their eyes – on their own devices. David Holmes brings over 20 years of high-tech marketing leadership to OutSystems. Prior to joining OutSystems, he was VP of Global Marketing for Damballa, a leading provider of network security solutions. Previously, he was SVP of Global Marketing for Jacada where his branding and positioning expertise helped drive the company from start-up days to a $55 million initial public offering on Nasdaq.
Performance is the intersection of power, agility, control, and choice. If you value performance, and more specifically consistent performance, you need to look beyond simple virtualized compute. Many factors need to be considered to create a truly performant environment. In his General Session at 14th Cloud Expo, Marc Jones, Vice President of Product Innovation for SoftLayer, will explain how to take advantage of a multitude of compute options and platform features to make cloud the cornerstone of your online presence.
Are you interested in accelerating innovation, simplifying deployments, reducing complexity, and lowering development costs? The cloud is changing the face of application development and deployment, with enterprise-grade infrastructure and platform services making it possible for you to build and rapidly scale enterprise applications. In his session at 14th Cloud Expo, Gene Eun, Sr. Director, Oracle Cloud at Oracle, will discuss the latest solutions and strategies for application developers and enterprise IT organizations to leverage Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) to build and deploy modern business applications in the cloud.
Hybrid cloud refers to the federation of a public and private cloud environment for the purpose of extending the elastic and flexibility of compute, storage and network capabilities, in an on-demand, pay-as-you go basis. The hybrid approach allows a business to take advantage of the scalability and cost-effectiveness that a public cloud computing environment offers without exposing mission-critical applications and data to third-party vulnerabilities. Hybrid cloud environments involve complex management challenges. First, organizations struggle to maintain control over the resources that lie outside of their managed IT scope. They also need greater infrastructure visibility to help reduce maintenance costs and ensure that their company data and resources are properly handled and secured.
As more applications and services move "to the cloud" (public or on-premise), cloud environments are increasingly adopting and building out traditional enterprise features. This in turn is enabling and encouraging cloud adoption from enterprise users. In many ways the definition is blurring as features like continuous operation, geo-distribution or on-demand capacity become the norm. At NuoDB we're involved in both building enterprise software and using enterprise cloud capabilities. In his session at 14th Cloud Expo, Seth Proctor, CTO of NuoDB, Inc., will cover experiences from building, deploying and using enterprise services and suggest some ways to approach moving enterprise applications into a cloud model.