Welcome!

Microservices Expo Authors: Liz McMillan, Elizabeth White, Roger Strukhoff, Pat Romanski, Carmen Gonzalez

Related Topics: @CloudExpo, Java IoT, Microservices Expo, Containers Expo Blog, Release Management , Apache

@CloudExpo: Blog Post

Cloudera Impala – Closing the Near Real Time Gap Working with Big Data

Building data structures and loading data

By

On October 24, 2012 Cloudera announced the release of Cloudera Impala and the commercial support subscription service of Cloudera Enterprise Real Time Query (RTQ). During the Hadoop World/STRATA Conference in NYC, I was invited over to see a demonstration. Impala is a SQL based Real Time Query/Ad Hoc query engine built on top of HDFS or Hbase. As I watched the demonstration unfold, I wondered if one of the remaining technology gaps in the NOSQL arsenal had been closed.  What gap you ask? Near Real Time Analytics on a NOSQL stack. Working with customers across the Cyber Security customer space, not only do they face the familiar BIGDATA horsemen of the apocalypse: Volume, Velocity and Variety but one more large challenge crept in: Time (V3T).  The Near Real Time Analysis/Near Real Time Analytic capability that Cloudera Impala provides is essential in many high value use cases associated with Cyber Security: comparing current activity with observed historical norms, correlation of many disparate data sources/enrichment and automated threat detection algorithms.

When the demonstration concluded, the Cloudera representatives and I discussed the potential of performing an informal independent evaluation of Cloudera Impala against some of the common Real Time/Near Real Time use cases in Cyber Security. I agreed to step up and perform an independent evaluation as well as developing a demonstration platform for FedCyber 2012 (almost three weeks hence for inquiring minds).  So let us set the field: a new BETA technology, NO prior exposure to the technology or documentation, a vendor making promises, addressing a large technology gap and three weeks to implement, seemed straight forward; no pressure.

The day after I returned from the STRATA Conference, I returned to my office and provisioned four Virtual Machines in order to build the Impala demonstration. As a committer/contributor for SherpaSurfing an open source Cyber Security solution, I have an abundance of data sets, enrichment sources, Hive data structures and services.  Given the amount of time and the audience for FedCyber 2012, I decided to focus on some Intrusion Detection and Netflow related use cases for the demonstration. The data sets for the demonstration included base data sets:  20 million Netflow events, 8 million Intrusion Detection System events and enrichment: Geographic, Blacklist, Whitelist and Protocol related information. Each of the selected uses cases for this demonstration is critical to the Perform Near-Real Time Network Analysis domain in Cyber Security. The name for the demonstration system was decided to be the Impala Mission Demonstration Platform (IMDP).  The IMDP was implemented based on vendor recommendations with no tuning or optimization.

The IMDP effort provided me with my first opportunity to work with Cloudera Manager. Although this post is focused on Cloudera Impala I would be remiss not to mention Cloudera Manager. I have worked with Hadoop since 1.0 and built more than a few clusters over the years. I used the installation and configuration guides provided with Cloudera Impala and followed the recommendations. One of the first recommendations was use of the Cloudera Manager. Using the Cloudera Manager (CDH 4.1), I was able to roll out a four node cluster in two hours.  I was able to discover the hosts, manage services and provision them in accordance with the IMDP deployment plan. The deployment plan consisted of:

  • node 1 – hbase, hdfs, impala,  mapreduce
  • node2 – hbase, hdfs, impala,  mapreduce
  • node3 – hbase(region server, master), hdfs(namenode), impala(impalad, statestore),  mapreduce(job tracker, tasktracker) , hue, oozie and zookeeper
  • node4 – Application Tier, Cloudera Manager

The Cloudera Manager saved at least two days of effort in deploying the cluster, the tight integration with the support portal, comprehensive help and one place to work with all properties of the entire cluster and view space consumption metrics; verdict on Cloudera Manager: Cloudera masterful, bold stroke, thumbs up.

Now that the cluster build-out completed; I shifted attention to deploying and configuring the Cloudera Impala service.  Using Cloudera Manager, I deployed Impala on three nodes: three instances of Impalad and one impala state store, in a matter of minutes. I completed the deployment and configuration of the Hive MetaStore. Keeping in mind this is a BETA; the documentation was complete, but fragmented on deployment and configuration (HIVE MetaStore portion); verdict on impala deployment and configuration: solid for a BETA (needs an example hive-site.xml, configuration guide needs better flow).

At this point all configuration and deployment was completed, attention turned to building data structures and loading data. I took the Data Definition Language (DDL) scripts or data structures for ten data sources and enrichment; ported them over to Hive and tested them in less than four hours. It is worthy of mention that the data sources for this demonstration are large flat tables: netflow and intrusion detection system. Cloudera Impala uses HIVE as an Extract Transform Load (ETL) engine, using Hive I defined all of the data structures in source files which were sourced using hive shell: created a database (Sherpa). Hive was then used to load data into the tables that were just created. Creating data structures in Hive was simple as usual and loading data sets was quick (20 million netflow events in 57 seconds). Logging into impala-shell, issued a refresh of the MetaStore and I was working with data. I performed verification of the data load, all data loaded and no issues were revealed. One area of potential improvement would be more comprehensive messages on load failure. Defining the data structures and loading data using Hive was nothing new; verdict:  really good; easy to use, easy to load, but need to improve failed load messages.

Finally, we moved on to the most interesting stage which is using Cloudera Impala in a series of Real Time Query (RTQ) scenarios that are common across the Cyber Security customer space. The real world scenarios selected come from the perform netflow analysis set of use case(s). In each of these scenarios, the exact same queries were executed on the same cluster using Hive and then Impala against the same data structures (database and tables).  In the Hive approach, we traverse the batch processing stack and with Impala we traverse the Real Time Query (RTQ) stack performing a series of analytics. In the first use case, I ran a five tuple (sip, sport, dip, dport, protocol) summary covering bytes per packet, summing bytes and packets for a 20 million event set resulted in: identical result sets, Hive 82 seconds – Impala 6 seconds.   In the second use case, I performed a summary of destination ports where the source port is 80 which resulted in: identical result sets, Hive 57 seconds, Impala 5 seconds. In the third use case, I performed correlation between netflow and intrusion detection systems, correlating netflow with intrusion detection events for several hours which resulted in: identical result sets, Hive 40 seconds, Impala sub-second.  Finally, for FedCyber 2012, I developed a java based situational awareness dashboard which connected to Cloudera Impala via ODBC and executed analytics performing: correlation of blacklists, Intrusion Detection, Netflow, statistical cubes for ten hours with a refresh of every five seconds without failure or issue.  The ODBC implementation easily provided the ability to export data to desktop tools (using ODBC) and common BI tools as advertised. Developing and Using Cloudera Impala verdict: This is as advertised; easy to use, easy to implement on, very fast, very flexible and more than capable of running real time analytics. The Impala shell is limited but much of the demonstration work was done using result sets so it was not an impediment.

In summation, I have worked for over a decade across the vast BIGDATA technology space covering Legacy Relational Database, Data Warehouse, and NOSQL; Cloudera Impala proved more than capable of running near real time analytics and providing mission relevance to customers with a Near Real Time (NRT) requirement.  Based on my initial review Cloudera Impala appears to be a bold step in closing the gap of near real time analytics on a NOSQL stack. I did encounter some minor problems, but the few problems and limitations that were encountered in this demonstration were documented and published in the known issues document so they will not be shared; none were show stoppers.

The notes, details and all of the lessons learned, data structures and the configuration guide from the demonstration are being published out on Github under SherpaSurfing in the coming days. These documents cover everything in detail and will enable developers to replicate the demonstration platform and get a jump start on Cloudera Impala.  Finally, I would like to thank two contributors: Hanh Le, Robert Webb and Six3 Systems for helping me pull this off.

Read the original blog entry...

More Stories By Bob Gourley

Bob Gourley writes on enterprise IT. He is a founder and partner at Cognitio Corp and publsher of CTOvision.com

@MicroservicesExpo Stories
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, discussed what every business should plan for how to structure their teams to delive...
Rapid innovation, changing business landscapes, and new IT demands force businesses to make changes quickly. In the eyes of many, containers are at the brink of becoming a pervasive technology in enterprise IT to accelerate application delivery. In this presentation, attendees learned about the: The transformation of IT to a DevOps, microservices, and container-based architecture What are containers and how DevOps practices can operate in a container-based environment A demonstration of how ...
As we enter the final week before the 19th International Cloud Expo | @ThingsExpo in Santa Clara, CA, it's time for me to reflect on six big topics that will be important during the show. Hybrid Cloud This general-purpose term seems to provide a comfort zone for many enterprise IT managers. It sounds reassuring to be able to work with one of the major public-cloud providers like AWS or Microsoft Azure while still maintaining an on-site presence.
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, Phil Hombledal, Solution Architect at CollabNet, discussed how customers are able to achieve a level of transparency that e...
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, showed how, by focusing on 'metrics that matter,' you can provide objective, transparent, and meaningful f...
Between 2005 and 2020, data volumes will grow by a factor of 300 – enough data to stack CDs from the earth to the moon 162 times. This has come to be known as the ‘big data’ phenomenon. Unfortunately, traditional approaches to handling, storing and analyzing data aren’t adequate at this scale: they’re too costly, slow and physically cumbersome to keep up. Fortunately, in response a new breed of technology has emerged that is cheaper, faster and more scalable. Yet, in meeting these new needs they...
@DevOpsSummit taking place June 6-8, 2017 at Javits Center, New York City, is co-located with the 20th International Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. @DevOpsSummit at Cloud Expo New York Call for Papers is now open.
Logs are continuous digital records of events generated by all components of your software stack – and they’re everywhere – your networks, servers, applications, containers and cloud infrastructure just to name a few. The data logs provide are like an X-ray for your IT infrastructure. Without logs, this lack of visibility creates operational challenges for managing modern applications that drive today’s digital businesses.
Today we can collect lots and lots of performance data. We build beautiful dashboards and even have fancy query languages to access and transform the data. Still performance data is a secret language only a couple of people understand. The more business becomes digital the more stakeholders are interested in this data including how it relates to business. Some of these people have never used a monitoring tool before. They have a question on their mind like “How is my application doing” but no id...
Information technology is an industry that has always experienced change, and the dramatic change sweeping across the industry today could not be truthfully described as the first time we've seen such widespread change impacting customer investments. However, the rate of the change, and the potential outcomes from today's digital transformation has the distinct potential to separate the industry into two camps: Organizations that see the change coming, embrace it, and successful leverage it; and...
In IT, we sometimes coin terms for things before we know exactly what they are and how they’ll be used. The resulting terms may capture a common set of aspirations and goals – as “cloud” did broadly for on-demand, self-service, and flexible computing. But such a term can also lump together diverse and even competing practices, technologies, and priorities to the point where important distinctions are glossed over and lost.
Monitoring of Docker environments is challenging. Why? Because each container typically runs a single process, has its own environment, utilizes virtual networks, or has various methods of managing storage. Traditional monitoring solutions take metrics from each server and applications they run. These servers and applications running on them are typically very static, with very long uptimes. Docker deployments are different: a set of containers may run many applications, all sharing the resource...
Keeping pace with advancements in software delivery processes and tooling is taxing even for the most proficient organizations. Point tools, platforms, open source and the increasing adoption of private and public cloud services requires strong engineering rigor – all in the face of developer demands to use the tools of choice. As Agile has settled in as a mainstream practice, now DevOps has emerged as the next wave to improve software delivery speed and output. To make DevOps work, organization...
Join Impiger for their featured webinar: ‘Cloud Computing: A Roadmap to Modern Software Delivery’ on November 10, 2016, at 12:00 pm CST. Very few companies have not experienced some impact to their IT delivery due to the evolution of cloud computing. This webinar is not about deciding whether you should entertain moving some or all of your IT to the cloud, but rather, a detailed look under the hood to help IT professionals understand how cloud adoption has evolved and what trends will impact th...
Internet of @ThingsExpo, taking place June 6-8, 2017 at the Javits Center in New York City, New York, is co-located with the 20th International Cloud Expo and will feature technical sessions from a rock star conference faculty and the leading industry players in the world. @ThingsExpo New York Call for Papers is now open.
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 session at @DevOpsSummit 19th Cloud Expo, Eric Robertson, General Manager at CollabNet, showed how customers are able to achieve a level of transparency that enables everyone fro...
You have great SaaS business app ideas. You want to turn your idea quickly into a functional and engaging proof of concept. You need to be able to modify it to meet customers' needs, and you need to deliver a complete and secure SaaS application. How could you achieve all the above and yet avoid unforeseen IT requirements that add unnecessary cost and complexity? You also want your app to be responsive in any device at any time. In his session at 19th Cloud Expo, Mark Allen, General Manager of...
The 20th International Cloud Expo has announced that its Call for Papers is open. Cloud Expo, to be held June 6-8, 2017, at the Javits Center in New York City, brings together Cloud Computing, Big Data, Internet of Things, DevOps, Containers, Microservices and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding business opportunity. Submit your speaking proposal ...
"Dice has been around for the last 20 years. We have been helping tech professionals find new jobs and career opportunities," explained Manish Dixit, VP of Product and Engineering at Dice, in this SYS-CON.tv interview at 19th Cloud Expo, held November 1-3, 2016, at the Santa Clara Convention Center in Santa Clara, CA.
In his session at 19th Cloud Expo, Claude Remillard, Principal Program Manager in Developer Division at Microsoft, contrasted how his team used config as code and immutable patterns for continuous delivery of microservices and apps to the cloud. He showed how 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 also demoed building immutable pipelines in the cloud ...