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Cutting Big Data Costs: Effective Data Processing With Apache Spark

DZone

In today's data-driven world, efficient data processing plays a pivotal role in the success of any project. Apache Spark , a robust open-source data processing framework, has emerged as a game-changer in this domain.

Big Data 279
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In-Stream Big Data Processing

Highly Scalable

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. The engine should be compact and efficient, so one can deploy it in multiple datacenters on small clusters. High performance and mobility.

Big Data 154
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Offline Data Pipeline Best Practices Part 1:Optimizing Airflow Job Parameters for Apache Hive

DZone

In this kickoff post, we delve into the intricacies of Apache Airflow and AWS EMR, a managed cluster platform for big data processing. Working together, they form the backbone of many modern data engineering solutions.

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What is software automation? Optimize the software lifecycle with intelligent automation

Dynatrace

Software analytics offers the ability to gain and share insights from data emitted by software systems and related operational processes to develop higher-quality software faster while operating it efficiently and securely. This involves big data analytics and applying advanced AI and machine learning techniques, such as causal AI.

Software 187
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What is IT automation?

Dynatrace

And what are the best strategies to reduce manual labor so your team can focus on more mission-critical issues? Ultimately, IT automation can deliver consistency, efficiency, and better business outcomes for modern enterprises. IT automation tools can achieve enterprise-wide efficiency. Big data automation tools.

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An overview of end-to-end entity resolution for big data

The Morning Paper

An overview of end-to-end entity resolution for big data , Christophides et al., It’s an important part of many modern data workflows, and an area I’ve been wrestling with in one of my own projects. Dynamic approaches schedule block processing on the fly to maximise efficiency. ACM Computing Surveys, Dec.

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Experiences with approximating queries in Microsoft’s production big-data clusters

The Morning Paper

Experiences with approximating queries in Microsoft’s production big-data clusters Kandula et al., Microsoft’s big data clusters have 10s of thousands of machines, and are used by thousands of users to run some pretty complex queries. All three sampling strategies are heavily used at Microsoft. VLDB’19.