Data Workflows with GCP Dataproc, Apache Airflow and Apache Spark
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Updated
Mar 4, 2020 - Python
Data Workflows with GCP Dataproc, Apache Airflow and Apache Spark
Projeto do Curso "Criando um Ecossistema Hadoop Totalmente Gerenciado com Google Cloud Dataproc" do Bootcamp Data Engineer da Digital Innovation One
Creating gcloud dataproc cluster with this github action
Deploying production ready environment for Spark cluster
Determination of which words occur in a dataset of textbooks along with each word's occurrence count identification with the help of Google Cloud Platform based Dataproc cluster formation.
Kaggle - Outbrain Click Prediction (Oct-2016 - Jan-2017)
Training a classification model as a Dataproc Job and using Kafka/PubSub connector for real-time prediction using pre-trained models
Yelp ETL Pipeline in Apache Spark on Google Cloud Dataproc
Content about how to create big data ecosystems on the Cloud
GCP_Data_Enginner
PySpark Job that runs in Dataproc cluster, loads data from Cloud Storage to BigQuery table.
Collection of personal resources on Google Cloud
Criando um ecossitema Hadoop totalmente gerenciado com Google Cloud Platform: O desafio consiste em efetuar um processamento de dados utilizando o produto Dataproc do GCP. Esse processamento irá efetuar a contagem das palavras de um livro e informar quantas vezes cada palavra aparece no mesmo.
Data Science Project: Predicting voter turnout in swing states in the United States based on 2020 General Election data through big data analytics
A Scala Spark based project to experiment with map-reduce algorithms on big data graph shaped
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.
Scheduling Big Data Workloads and Data Pipelines in the Cloud with pyDag
Run Jupyter Notebooks (and store data) on Google Cloud Platform.
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