Remove Big Data Remove Efficiency Remove Latency
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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. This system has been designed to supplement and succeed the existing Hadoop-based system that had too high latency of data processing and too high maintenance costs. Pipelining.

Big Data 154
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Understanding gRPC Concepts, Use Cases, and Best Practices

DZone

This leads to an increase in the size of data as well. Big data is generated and transported using various mediums in single requests. With the increase in the size of data, we have activities like serializing, deserializing, and transportation costs added to it. We need to cut down on transportation.

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Investigation of a Workbench UI Latency Issue

The Netflix TechBlog

Overview At Netflix, the Analytics and Developer Experience organization, part of the Data Platform, offers a product called Workbench. Workbench is a remote development workspace based on Titus that allows data practitioners to work with big data and machine learning use cases at scale. We then exported the .har

Latency 210
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Bulldozer: Batch Data Moving from Data Warehouse to Online Key-Value Stores

The Netflix TechBlog

Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy. The processed data is typically stored as data warehouse tables in AWS S3. Moving data with Bulldozer at Netflix.

Latency 248
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What is a data lakehouse? Combining data lakes and warehouses for the best of both worlds

Dynatrace

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. What is a data lakehouse? Data warehouses.

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No need to compromise visibility in public clouds with the new Azure services supported by Dynatrace

Dynatrace

Our customers have frequently requested support for this first new batch of services, which cover databases, big data, networks, and computing. See the health of your big data resources at a glance. Azure HDInsight supports a broad range of use cases including data warehousing, machine learning, and IoT analytics.

Azure 227
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Evolving from Rule-based Classifier: Machine Learning Powered Auto Remediation in Netflix Data…

The Netflix TechBlog

Operational automation–including but not limited to, auto diagnosis, auto remediation, auto configuration, auto tuning, auto scaling, auto debugging, and auto testing–is key to the success of modern data platforms. the retry success probability) and compute cost efficiency (i.e., Multi-objective optimizations.

Tuning 213