Cloudera

FEBRUARY 14, 2024

Introduction Apache Iceberg has recently grown in popularity because it adds data warehouse-like capabilities to your data lake making it easier to analyze all your data — structured and unstructured. However, you need to regularly maintain Iceberg tables to keep them in a healthy state so that read queries can perform faster.

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Bytes Metadata Data Lake SQL 57

ProjectPro

FEBRUARY 8, 2023

Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Furthermore, Glue supports databases hosted on Amazon Elastic Compute Cloud (EC2) instances on an Amazon Virtual Private Cloud, including MySQL, Oracle, Microsoft SQL Server, and PostgreSQL.

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ProjectPro

NOVEMBER 22, 2021

PySpark runs a completely compatible Python instance on the Spark driver (where the task was launched) while maintaining access to the Scala-based Spark cluster access. This enables them to integrate Spark's performant parallel computing with normal Python unit testing. Is PySpark the same as Spark? appName('ProjectPro').getOrCreate()

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Hadoop Python Datasets Metadata 52

ProjectPro

JANUARY 31, 2023

HBase storage is ideal for random read/write operations, whereas HDFS is designed for sequential processes. Typically, data processing is done using frameworks such as Hadoop, Spark, MapReduce, Flink, and Pig, to mention a few. Commodity hardware is the fundamental hardware resource required to operate the Apache Hadoop framework.

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Big Data Hadoop AWS Relational Database 52

ProjectPro

JUNE 4, 2015

In our earlier articles, we have defined “What is Apache Hadoop” To recap, Apache Hadoop is a distributed computing open source framework for storing and processing huge unstructured datasets distributed across different clusters. Table of Contents Big Data Hadoop Training Videos- What is Hadoop and its popular vendors?

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Hadoop Architecture IT Java 52

Cloudera

DECEMBER 15, 2020

Across nearly every sector working with complex data, Spark has quickly become the de-facto distributed computing framework for teams across the data and analytics lifecycle. One of most awaited features of Spark 3.0 For a deeper look at the framework, take our updated Apache Spark Performance Tuning course.

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SQL Datasets Designing Process 97

ProjectPro

AUGUST 21, 2015

Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. Speed Writes are Fast Reads are Fast Master Big Data with Real-World Hadoop Projects 2. Data Serialization Components are - Thrift and Avro Data Intelligence Components are - Apache Mahout and Drill.

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Hadoop Big Data Metadata Java 40