Remove Events Remove Hadoop Remove Metadata Remove Structured Data
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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

AltexSoft

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

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Mastering the Art of ETL on AWS for Data Management

ProjectPro

Data integration with ETL has evolved from structured data stores with high computing costs to natural state storage with read operation alterations thanks to the agility of the cloud. Data integration with ETL has changed in the last three decades. AWS Glue has a central metadata repository called the Glue catalog.

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Hadoop vs Spark: Main Big Data Tools Explained

AltexSoft

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. What are its limitations and how do the Hadoop ecosystem address them? What is Hadoop.

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Sqoop vs. Flume Battle of the Hadoop ETL tools

ProjectPro

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment.

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The Good and the Bad of Apache Spark Big Data Processing

AltexSoft

Spark SQL brings native support for SQL to Spark and streamlines the process of querying semistructured and structured data. Datasets: RDDs can contain any type of data and can be created from data stored in local filesystems, HDFS (Hadoop Distributed File System), databases, or data generated through transformations on existing RDDs.

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Data Lake vs Data Warehouse - Working Together in the Cloud

ProjectPro

Is Snowflake a data lake or data warehouse? Is Hadoop a data lake or data warehouse? This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data from data warehouses is queried using SQL.

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50 PySpark Interview Questions and Answers For 2023

ProjectPro

StructType is a collection of StructField objects that determines column name, column data type, field nullability, and metadata. PySpark imports the StructType class from pyspark.sql.types to describe the DataFrame's structure. The uName and the event timestamp are then combined to make a tuple. appName('ProjectPro').getOrCreate()

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