Performance Observability for Apache Spark

An end to end demo of Google's Cloud data and analytic stack.

Companion to Learning Hadoop and Learning Spark courses on Linked In Learning

Ephemeral Hadoop clusters using Google Compute Platform

A Python framework for data processing on GCP.

Solution Accelerators for Serverless Spark on GCP, the industry's first auto-scaling and serverless Spark as a service

EtlFlow is an ecosystem of functional libraries in Scala based on ZIO for running complex Auditable workflows which can interact with Google Cloud Platform, AWS, Kubernetes, Databases, SFTP servers, On-Prem Systems and more.

gomrjob - a Go Framework for Hadoop Map Reduce Jobs

Debussy is an opinionated Data Architecture and Engineering framework, enabling data analysts and engineers to build better platforms and pipelines.

Data Pipeline from the Global Historical Climatology Network DataSet

Scheduling Big Data Workloads and Data Pipelines in the Cloud with pyDag

This repository is deprecated. All of its content and history has been moved to googleapis/google-cloud-node.

Creating an Inverted Index of words occurring in a large set of documents extracted from web pages using Hadoop MapReduce and Google Dataproc

Dataproc Scala Examples is an effort to assist in the creation of Spark jobs written in Scala to run on Dataproc.

ecommerce GCP Streaming pipeline ― Cloud Storage, Compute Engine, Pub/Sub, Dataflow, Apache Beam, BigQuery and Tableau; GCP Batch pipeline ― Cloud Storage, Dataproc, PySpark, Cloud Spanner and Tableau

A search engine to query social media insights with political theme

An educational project to build an end-to-end pipline for near real-time and batch processing of data further used for visualisation and a machine learning model.

GCP_Data_Enginner

opens a chrome browser to a dataproc cluster

Demonstration of Google Cloud Dataproc Workflow Templates