Systems | Development | Analytics | API | Testing

Applying Fine Grained Security to Apache Spark

Apache Spark with its rich data APIs has been the processing engine of choice in a wide range of applications from data engineering to machine learning, but its security integration has been a pain point.t Many enterprise customers needi finer granularity of control, in particular at the column and row level (commonly known as Fine Grained Access Control or FGAC).

Fine-Tune Fair to Capacity Scheduler in Weight Mode

Cloudera Data Platform (CDP) unifies the technologies from Cloudera Enterprise Data Hub (CDH) and Hortonworks Data Platform (HDP). As part of that unification process, Cloudera merged the YARN Scheduler functionality from the legacy platforms, creating a Capacity Scheduler that better services all customers. In merging this scheduler functionality, Cloudera significantly reduced the time and effort to migrate from CDH and HDP.

Industry Impact | Data-Driven Digital Transformation

Data is more than ones and zeroes. If you can put it to work, data has the power to transform your entire company, even your entire industry. With more than 2000 customers in over 85 countries, Cloudera is helping companies across industries generate more revenue, build new products and understand their customers at scale and speed.

Driving Success With a Modern Data Architecture and a Hybrid Approach in the Financial Services and Telco Industries

Corporations are generating unprecedented volumes of data, especially in industries such as telecom and financial services industries (FSI). Many organizations are hoping to leverage these massive amounts of data by investing heavily in big data solutions – solutions that they hope can meet business goals such as increasing customer satisfaction, uncovering alternative revenue streams, or improving operational efficiency.

Commands: Debug and Property Update

The support of remote issue observation, investigation and possibly resolution is a powerful new feature of Edge Flow Manager. This video shows a case where the user observes a problem via the Agent Manager UI, is able to collect additional information using the Debug Command which provides configuration, property and logs from the observed agent and in this particular case is able to resolve the issue by using the Property Update Command to reconfigure the agent remotely.

Flow Creation in Edge Flow Manager

This video shows the usage of Edge Flow Manager’s flow designer and using the example flow it explains the concept of agent classes and publishing. It goes through the Dashboard view for agent classes and the canvas for the flow designer where processors, remote process groups and funnels are also explained. To see all of this in action, a very basic flow is created with two processors and published to the MiNiFi agents under the agent class the flow is designed for. After publishing, the means of tracking the flow deployment progress are also covered.

Simplify Metrics on Apache Druid With Rill Data and Cloudera

Co-author: Mike Godwin, Head of Marketing, Rill Data Cloudera has partnered with Rill Data, an expert in metrics at any scale, as Cloudera’s preferred ISV partner to provide technical expertise and support services for Apache Druid customers. We want Cloudera customers that rely on Apache Druid to know that their clusters are secure and supported by the Cloudera partner ecosystem.

Does Financial Crime Increase During a Recession?

The dynamic and interconnected world of global ecommerce, crypto currencies, and alternative payments places increased pressure on anti-financial crime measures to keep pace and transform alongside these initiatives. Consumers worldwide are projected to use mobile devices to make more than 30.7 billion ecommerce transactions by 2026, a five-fold increase over the 6.1 billion predicted for 2022.

Fraud Detection With Cloudera Stream Processing Part 2: Real-Time Streaming Analytics

In part 1 of this blog we discussed how Cloudera DataFlow for the Public Cloud (CDF-PC), the universal data distribution service powered by Apache NiFi, can make it easy to acquire data from wherever it originates and move it efficiently to make it available to other applications in a streaming fashion.

Differences between the C++ and Java MiNiFi agents

In this video we will go through all the differences between the C++ and Java MiNiFi agents. The video shows the differences observed on the Edge Flow Manager UI ranging from different information to the presence of buttons and dropdown elements determined by the agent type. Differences in feature set and functionality are also highlighted. The two implementations also have different footprints (memory and CPU) as well as a different set of available components. This video will help you determine the MiNiFi agent that best suits your use case.