Welcome!

Related Topics: @BigDataExpo, Apache

@BigDataExpo: Blog Post

An Example to Illustrate Hadoop Code Reuse

The developer tool to realize Hadoop code reuse

The MapReduce of Hadoop is a widely-used parallel computing framework. However, its code reuse mechanism is inconvenient, and it is quite cumbersome to pass parameters. Far different from our usual experience of calling the library function easily, I found both the coder and the caller must bear a sizable amount of precautions in mind when writing even a short pieces of program for calling by others.

However, we finally find that esProc could easily realize code reuse in hadoop. Still a simple and understandable example of grouping and summarizing, let's check out a solution with not so great reusability. Suppose we need to group the big data of order (sales.txt) on HDFS by salesman (empID), and seek the corresponding sales amount of each Salesman. esProc codes are:
Code for summary machine:



Code for node machine:



esProc classifies the distributed computing into two categories: The respective codes for summary machine and node machine. The summary machine is responsible for task scheduling, distributing the task to every task in the form of parameter, and finally integrating and summarizing the computing results from node machines. The node machines are used to get a segment of the whole data piece as specified by parameters, and then group and summarize the data of this segment.

As can be seen, esProc code is intuitive and straightforward, just like the natural and common thinking patterns. The summary machine distributes a task into several segments; distributes them to the unit machine to summarize initially; and then further summarizes the summary machine for the second time. Another thing to note is the esProc grouping and summarizing function "groups", which is used to perform the grouping action over the two-dimensional table A1 by empID and sum up the values of amount fields. The result will be renamed to the understandable totalAmount. This whole procedure of grouping and summarizing is quite concise and intuitive: A1.groups(empID;sum(amount): totalAmount)

In addition, the groups function can be applied to not only the small 2D table, but also the 2D table that is too great to be held in the memory. For example, the cursor mode is adopted for the above codes.

But there are some obvious defects in the above example: The reusability of code is not great. In the steps followed, we will rewrite the above example to a universal algorithm independent of any concrete business. It will be rewritten to control the code flow with parameters, so as to summarize whatsoever data file. In which, the task granularity can be scheduled into arbitrary number of segments, and the computing nodes can be specified at will. Then, the revised codes are shown below:

Code for summary machine. There are altogether 4 parameters defined here: fileName: Big data file to analyze; taskNumber: Number of tasks to distribute; groupField: Fields to group; sumField: Fields to summarize. In addition, the node machine is obtained via reading the profiles.



Code for node machine. In the revised codes, 4 variables are used to receive the parameter from summary machine. Besides the file starting and ending positions (start and end) from the first example, there are two newly-added fields. They are groupField: Fields to group; and sumField: Fields to summarize.



In esProc, it is much easier to pass and use parameter because users can implement the common grouping and summarizing with the least modification workload, and reuse the codes easily.

In Hadoop, the complicated business algorithm is mainly implemented by writing the MapReduce class. By comparison, it is much more inflexible to pass and use parameters in MapReduce. Though it is possible to implement a flexible algorithm independent of the concrete business, it is really cumbersome. Judging the Hadoop codes, the coupling degree of code and business is great. To pass the parameters, a global-variable-like mechanism is required, which is not only inconvenient but also hard to understand. That's why so many questions about MapReduce parameter-passing are here and there on many Web pages. Lots of people feel confused about developing universal algorithms with MapReduce.

In addition, the default separator in the above codes is the comma. It is obvious that users only need to add a variable in a similar way to customize it to any more commonly-used symbol. With it, they can also implement the common action of data filtering and then grouping and summarizing easily. Please note the usage of parameter groupField. It is used as the character parameter in the cell A6, but the macro in A8. In other words, ${gruopField} can be resolved as the formula itself, instead of any parameter in the formula alone. This is the work of dynamic language. Therefore, esProc can realize the completely flexible code, for example, using the parameter to control the summary algorithm to perform sum up or just count, seek the average value or maximum.

"Macro" is a simple special case of dynamic language. esProc supports a more flexible and complete dynamic language system.

As you may find from the above example, esProc can implement Hadoop code reuse easily, and basically achieve the goal of "Write once, run anywhere!". Needless to say, the development efficiency can be boosted dramatically.

personal blog: http://datakeyword.blogspot.com/

website: http://www.raqsoft.com/

More Stories By Jessica Qiu

Jessica Qiu is the editor of Raqsoft. She provides press releases for data computation and data analytics.

Latest Stories
DX World EXPO, LLC., a Lighthouse Point, Florida-based startup trade show producer and the creator of "DXWorldEXPO® - Digital Transformation Conference & Expo" has announced its executive management team. The team is headed by Levent Selamoglu, who has been named CEO. "Now is the time for a truly global DX event, to bring together the leading minds from the technology world in a conversation about Digital Transformation," he said in making the announcement.
"We've been engaging with a lot of customers including Panasonic, we've been involved with Cisco and now we're working with the U.S. government - the Department of Homeland Security," explained Peter Jung, Chief Product Officer at Pulzze Systems, in this SYS-CON.tv interview at @ThingsExpo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"We're here to tell the world about our cloud-scale infrastructure that we have at Juniper combined with the world-class security that we put into the cloud," explained Lisa Guess, VP of Systems Engineering at Juniper Networks, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"Peak 10 is a hybrid infrastructure provider across the nation. We are in the thick of things when it comes to hybrid IT," explained , Chief Technology Officer at Peak 10, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"I will be talking about ChatOps and ChatOps as a way to solve some problems in the DevOps space," explained Himanshu Chhetri, CTO of Addteq, in this SYS-CON.tv interview at @DevOpsSummit at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"We are focused on SAP running in the clouds, to make this super easy because we believe in the tremendous value of those powerful worlds - SAP and the cloud," explained Frank Stienhans, CTO of Ocean9, Inc., in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
While the focus and objectives of IoT initiatives are many and diverse, they all share a few common attributes, and one of those is the network. Commonly, that network includes the Internet, over which there isn't any real control for performance and availability. Or is there? The current state of the art for Big Data analytics, as applied to network telemetry, offers new opportunities for improving and assuring operational integrity. In his session at @ThingsExpo, Jim Frey, Vice President of S...
"As we've gone out into the public cloud we've seen that over time we may have lost a few things - we've lost control, we've given up cost to a certain extent, and then security, flexibility," explained Steve Conner, VP of Sales at Cloudistics,in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
Your homes and cars can be automated and self-serviced. Why can't your storage? From simply asking questions to analyze and troubleshoot your infrastructure, to provisioning storage with snapshots, recovery and replication, your wildest sci-fi dream has come true. In his session at @DevOpsSummit at 20th Cloud Expo, Dan Florea, Director of Product Management at Tintri, provided a ChatOps demo where you can talk to your storage and manage it from anywhere, through Slack and similar services with...
The financial services market is one of the most data-driven industries in the world, yet it’s bogged down by legacy CPU technologies that simply can’t keep up with the task of querying and visualizing billions of records. In his session at 20th Cloud Expo, Karthik Lalithraj, a Principal Solutions Architect at Kinetica, discussed how the advent of advanced in-database analytics on the GPU makes it possible to run sophisticated data science workloads on the same database that is housing the rich...
"At the keynote this morning we spoke about the value proposition of Nutanix, of having a DevOps culture and a mindset, and the business outcomes of achieving agility and scale, which everybody here is trying to accomplish," noted Mark Lavi, DevOps Solution Architect at Nutanix, in this SYS-CON.tv interview at @DevOpsSummit at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"We are an IT services solution provider and we sell software to support those solutions. Our focus and key areas are around security, enterprise monitoring, and continuous delivery optimization," noted John Balsavage, President of A&I Solutions, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
"We want to show that our solution is far less expensive with a much better total cost of ownership so we announced several key features. One is called geo-distributed erasure coding, another is support for KVM and we introduced a new capability called Multi-Part," explained Tim Desai, Senior Product Marketing Manager at Hitachi Data Systems, in this SYS-CON.tv interview at 20th Cloud Expo, held June 6-8, 2017, at the Javits Center in New York City, NY.
There is a huge demand for responsive, real-time mobile and web experiences, but current architectural patterns do not easily accommodate applications that respond to events in real time. Common solutions using message queues or HTTP long-polling quickly lead to resiliency, scalability and development velocity challenges. In his session at 21st Cloud Expo, Ryland Degnan, a Senior Software Engineer on the Netflix Edge Platform team, will discuss how by leveraging a reactive stream-based protocol,...
DevOps at Cloud Expo, taking place October 31 - November 2, 2017, at the Santa Clara Convention Center in Santa Clara, CA, is co-located with 21st Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. The widespread success of cloud computing is driving the DevOps revolution in enterprise IT. Now as never before, development teams must communicate and collaborate in a dynamic, 24/7/365 environment. There is no time to w...