Knowledge Hut

MAY 2, 2024

Here come the frameworks like Apache Spark and MapReduce to our rescue and help us to get deep insights into this huge amount of structured, unstructured, and semi-structured data and make more sense of it. Since its launch Spark has seen rapid adoption and growth. billion (2019 – 2022).

Scala 96

Scala Hadoop Datasets Java 96

Towards Data Science

APRIL 30, 2024

Intro Google Dataflow is a fully managed data processing service that provides serverless unified stream and batch data processing. It is the first choice Google would recommend when dealing with a stream processing workload. If you want to learn more about stream processing, I strongly recommend this paper.

Google Cloud 61

Google Cloud Process Cloud Lambda Architecture 61

Knowledge Hut

DECEMBER 26, 2023

Also, read about what is markdown and, why should we use it. Where to take Training for Certification: KnowledgeHut has a comprehensive course structure for those who want to learn MongoDB & Mongodb Administrator. A certification from a reputed accreditation body will validate your skills and make you stand out among your peers.

Certification 98

Certification Programming MongoDB R (Programming) 98

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?

Hadoop 52

Hadoop Python Datasets Metadata 52

ProjectPro

JANUARY 31, 2023

Big data analytics analyzes structured and unstructured data to generate meaningful insights based on changing market trends, hidden patterns, and correlations. HBase storage is ideal for random read/write operations, whereas HDFS is designed for sequential processes. RDBMS stores structured data. RDBMS uses high-end servers.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

DECEMBER 7, 2021

To understand the working of a data pipeline, one can consider a pipe that receives input from a source that is carried to give output at the destination. In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. Data ingestion methods gather and bring data into a data processing system.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

NOVEMBER 15, 2021

Apache Beam Source: Google Cloud Platform Apache Beam is an advanced unified programming open-source model launched in 2016. It derives its name “Beam” which is from “Batch” + “Stream” from its functionalities for both batch and streaming the parallel processing pipelines for data.

Big Data 52

Big Data Project Metadata Programming Language 52