synapse-azure-data-explorer-101
azure-kusto-spark
Our great sponsors
| synapse-azure-data-explorer-101 | azure-kusto-spark | |
|---|---|---|
| 1 | 1 | |
| 4 | 74 | |
| - | - | |
| 0.0 | 6.4 | |
| almost 3 years ago | 3 days ago | |
| Jupyter Notebook | Scala | |
| - | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
synapse-azure-data-explorer-101
-
Getting started with Azure Data Explorer and Azure Synapse Analytics for Big Data processing
Notebooks are available in this GitHub repo — https://github.com/abhirockzz/synapse-azure-data-explorer-101
azure-kusto-spark
-
Getting started with Azure Data Explorer and Azure Synapse Analytics for Big Data processing
Azure Data Explorer is a fully managed data analytics service that can handle large volumes of diverse data from any data source, such as websites, applications, IoT devices, and more. Azure Data Explorer makes it simple to ingest this data and enables you to do complex ad hoc queries on the data in seconds. It scales quickly to terabytes of data, in minutes, allowing rapid iterations of data exploration to discover relevant insights. It is already integrated with Apache Spark work via the Data Source and Data Sink Connector and is used to power solutions for near real-time data processing, data archiving, machine learning etc.
What are some alternatives?
ngods-stocks - New Generation Opensource Data Stack Demo
deequ - Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.
project - Predict how many points an European football team will end the season with, according to the characteristics of its players. Project for the Big Data Computing course at Sapienza University of Rome (2021-22)
kusto-queries - example queries for learning the kusto language
dracula - a brief analysis to the most common words in Dracula, by Bram Stoker
SynapseML - Simple and Distributed Machine Learning
workshop-introduction-to-machine-learning - Come ready to discover the goals and approaches of machine learning, and how to build effective algorithms and solutions!
frameless - Expressive types for Spark.
project-atlas-sao-paulo - A project for the development of rich geospatial data from the city of São Paulo for use in Machine Learning models.
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
pyspark_nlp_workshop - Instructions and code for the workshop "From Big Data to NLP Insights: Unlocking the Power of PySpark and Spark NLP"