charlesb / CDF-workshopLinks
Leveraging Hortonworks' HDP 3.1.0 and HDF 3.4.0 components, this tutorial guides the user through steps to stream data from a REST API into a live dashboard using NiFi, Kafka, Hive LLAP with Druid integration and Superset. This workshop will also cover steps to remotely manage MiNiFi to send data to NiFi using Edge Flow Manager (EFM).
☆19Updated 6 years ago
Alternatives and similar repositories for CDF-workshop
Users that are interested in CDF-workshop are comparing it to the libraries listed below
Sorting:
- ☆27Updated 2 years ago
- TPCDS benchmark for various engines☆18Updated 3 years ago
- An Azure Databricks workshop leveraging the New York Taxi and Limousine Commission Trip Records dataset☆111Updated 2 years ago
- Edge2AI Workshop☆70Updated 7 months ago
- Apache Spark Connector for SQL Server and Azure SQL☆287Updated 11 months ago
- dbt adapter for Azure Synapse Dedicated SQL Pools☆76Updated 5 months ago
- Enabling Continuous Data Processing with Apache Spark and Azure Event Hubs☆238Updated 11 months ago
- Tools for Deploying Databricks Solutions in Azure☆96Updated 2 years ago
- How DevOps principles can be applied to Data Pipeline Solution built with Azure Databricks, Data Factory and ADL Gen2. Moved to: https://…☆62Updated last year
- Databricks Platform - Architecture, Security, Automation and much more!!☆52Updated last week
- An Azure Function which allows Azure Data Factory (ADF) to connect to Snowflake in a flexible way.☆26Updated 2 years ago
- Delta Lake Documentation☆53Updated last year
- SQL Queries & Alerts for Databricks System Tables access.audit Logs☆41Updated 6 months ago
- The Internals of Spark on Kubernetes☆72Updated 3 years ago
- Spark and Delta Lake Workshop☆22Updated 3 years ago
- Databricks Migration Tools☆43Updated 4 years ago
- Anomaly Detection Pipeline on Azure Databricks☆28Updated 6 years ago
- DataQuality for BigData☆147Updated 2 years ago
- Multi-stage, config driven, SQL based ETL framework using PySpark☆26Updated 6 years ago
- The Taxonomy for ETL Automation Metadata (TEAM) is a tool for design metadata management geared towards data warehouse automation. It is …☆37Updated last year
- Smart Automation Tool for building modern Data Lakes and Data Pipelines☆122Updated this week
- Nested Data (JSON/AVRO/XML) Parsing and Flattening in Spark☆16Updated 2 years ago
- Two-day level 300 Azure Synapse Analytics workshop☆11Updated 4 years ago
- Support for generating modern platforms dynamically with services such as Kafka, Spark, Streamsets, HDFS, ....☆80Updated last week
- Code samples, etc. for Databricks☆73Updated 8 months ago
- ☆76Updated last year
- Example code for doing DataOps☆49Updated 5 years ago
- Delta Lake examples☆238Updated last year
- Demo of using the Nutter for testing of Databricks notebooks in the CI/CD pipeline☆151Updated last year
- Testing framework for Databricks notebooks☆315Updated last year