| 1. A Quick Introduction to Apache Kafka.mp4 | 12.7 MB | ||
| 1. A Quick Introduction to Apache Pinot.mp4 | 16.2 MB | ||
| 1. A Quick Introduction to Apache Superset.mp4 | 5 MB | ||
| 1. Bonus Lecture.mp4 | 12.2 MB | ||
| 1. Congratulations.mp4 | 3.1 MB | ||
| 1. Course Introduction and Outcome.mp4 | 8.4 MB | ||
| 1. Flink Basic Concepts.mp4 | 36.2 MB | ||
| 1. Realtime Analytics for an Online Cab Service Company.mp4 | 15.2 MB | ||
| 10. Using Event Time Temporal Joins and Lookup Joins to Enrich Ride Data Hands On.mp4 | 313 MB | ||
| 11. Running Flink on a Cluster Hands On.mp4 | 119.8 MB | ||
| 12. Flink Quiz.html | 204.8 B | ||
| 2. Apache Pinot Setup Hands On.mp4 | 74.1 MB | ||
| 2. Architecture and Data Model for Realtime Analytics.mp4 | 25.8 MB | ||
| 2. Course Resources.html | 204.8 B | ||
| 2. Setting up Apache Superset Hands On.mp4 | 81.2 MB | ||
| 2. Using the Table API to Read from Kafka Hands On.mp4 | 103.5 MB | ||
| 2. What is Realtime Analytics and Why is it Needed.mp4 | 15.4 MB | ||
| 3. Architecture Quiz.html | 204.8 B | ||
| 3. Guide for Different Operating Systems.html | 921.6 B | ||
| 3. Helper for Different Operating Systems.html | 1.2 KB | ||
| 3. Pinot MacOS M1 & M2 Guideline.html | 307.2 B | ||
| 3. Realtime Analytics Quiz.html | 204.8 B | ||
| 3. Using Flink SQL to perform Transformations Hands On.mp4 | 26.2 MB | ||
| 4. Apache Kafka Setup Hands On.mp4 | 77.2 MB | ||
| 4. Checkpoints and Watermarks.mp4 | 19.4 MB | ||
| 4. Connecting Superset with Apache Pinot Hands On.mp4 | 62.7 MB | ||
| 4. Realtime Ingestion in Apache Pinot Hands On.mp4 | 51.7 MB | ||
| 5. Creating Realtime Analytics Dashboards in Superset.mp4 | 67 MB | ||
| 5. Data Production and Consumption from Apache Kafka Hands On.mp4 | 38.9 MB | ||
| 5. Flink Concepts Quiz.html | 204.8 B | ||
| 5. Upserts in Pinot.mp4 | 11.5 MB | ||
| 6. Kafka Quiz.html | 204.8 B | ||
| 6. Realtime Upserts for Enriched Ride Data in Apache Pinot Hands On.mp4 | 124 MB | ||
| 6. Regular Joins.mp4 | 12.3 MB | ||
| 6. Superset Quiz.html | 204.8 B | ||
| 7. Running Realtime Analytics Queries in Pinot Data Explorer Hands On.mp4 | 109.4 MB | ||
| 7. Temporal Joins.mp4 | 27.9 MB | ||
| 8. Mysql Installation Links for Different Operating Systems.html | 1 KB | ||
| 8. Querying Data through Pinot REST API.mp4 | 22.3 MB | ||
| 9. Apache Pinot Quiz.html | 204.8 B | ||
| 9. Setup MySQL for Location data Hands On.mp4 | 29.1 MB | ||
| Bonus Resources.txt | 409.6 B | ||
| FlinkSQLExample.java | 2 KB | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| RideEnrichApplication.java | 8 KB | ||
| TableAPIExample.java | 2 KB | ||
| dashboard_queries | 1.2 KB | ||
| driver.json | 102.4 B | ||
| driver_data.txt | 716.8 B | ||
| flink_helper.txt | 1 KB | ||
| flink_sql.txt | 512 B | ||
| kafka_helper.txt | 1.8 KB | ||
| main_logic.txt | 716.8 B | ||
| mysql_helper.txt | 921.6 B | ||
| output_data.txt | 102.4 B | ||
| pinot_helper.txt | 1.1 KB | ||
| pom.xml | 2.2 KB | ||
| queries.txt | 2.2 KB | ||
| ride.json | 307.2 B | ||
| ride_data.txt | 5.8 KB | ||
| rider.json | 102.4 B | ||
| rider_data | 716.8 B | ||
| rides_enriched_schema | 1.7 KB | ||
| rides_enriched_table | 2.6 KB | ||
| stream_ingestion.txt | 614.4 B | ||
| superset-helper.txt | 1.2 KB | ||
| table.txt | 3.2 KB | ||
| ▲ 67 total files | |||
Realtime Analytics with Apache Pinot and Apache Flink
https://DevCourseWeb.com
Published 2/2024
Created by Aditya S
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 34 Lectures ( 2h 59m ) | Size: 1.48 GB
Understand how Realtime Analytics can be done for a Real Industry Use case With Apache Pinot and Apache Flink
What you'll learn:
Understand how Realtime analytics can be done for a Real World business case of Online Cab Service Company
Understand how Apache Flink can be used for Realtime Data Processing
Understand how you can Join across multiple streams in Apache Flink
Learn how to Lookup data in Flink from external data stores
Learn how to Use Apache Pinot to run Realtime Analytical Queries
Learn how Realtime Upserts are possible in Apache Pinot
Learn how Apache Kafka acts as the Connecting layer between the various components in a Realtime Analytics System
Learn how to create Dashboards for Realtime data in Apache Superset
Everything in this course is use case focussed so that you can directly Apply this to a Real Life project
Requirements:
Having prior Knowledge of Java and SQL is helpful but not Mandatory
Everything is thought within the course itself, So no Prior background is needed
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