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3 Performance Tricks for Dealing With Big Data Sets

DZone

This article describes 3 different tricks that I used in dealing with big data sets (order of 10 million records) and that proved to enhance performance dramatically. Trick 1: CLOB Instead of Result Set.

Big Data 246
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Write Optimized Spark Code for Big Data Applications

DZone

Apache Spark is a powerful open-source distributed computing framework that provides a variety of APIs to support big data processing. PySpark is the Python API for Apache Spark , which allows Python developers to write Spark applications using Python instead of Scala or Java.

Big Data 161
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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

When handling large amounts of complex data, or big data, chances are that your main machine might start getting crushed by all of the data it has to process in order to produce your analytics results. Greenplum features a cost-based query optimizer for large-scale, big data workloads. Query Optimization.

Big Data 321
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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 269
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ScyllaDB Trends – How Users Deploy The Real-Time Big Data Database

Scalegrid

Google Cloud does offer their own wide column store and big data database called Bigtable which is actually ranked #111, one under ScyllaDB at #110 on DB-Engines. Google Cloud Platform (GCP) was the second most popular cloud provider for ScyllaDB, coming in at 30.4% of all cloud deployments.

Big Data 187
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How Amazon is solving big-data challenges with data lakes

All Things Distributed

Back when Jeff Bezos filled orders in his garage and drove packages to the post office himself, crunching the numbers on costs, tracking inventory, and forecasting future demand was relatively simple.

Big Data 209
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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. Other flows are more sophisticated: one Storm topology can pass the data to another topology via Kafka or Cassandra. Towards Unified Big Data Processing. Apache Spark [10].

Big Data 154