Spark, Hive, Flume, OOZIE
Online Delivery Service
Web & Mobile
- Client wanted to provide recommendations on products to end user, based on their search.
- Since they had large data sets, it was difficult to search fast and subsequently provide recommendation.
- Distributed storage and distributed processing of very large data sets as required to apply different analytical function.
- Solution was needed to process unstructured as well as real-time data feeds.
- We designed and developed web-based application to interface with user.
- It Integrates data from different data source using SQOOP.
- Gather real-time data feeds using flume and spark streaming.
- Store the unstructured data in HDFS and proceed further.
- Using OOZIE, to schedule different shell and Hadoop eco system jobs.
- Use spark-sql to perform analyzing operation.
Online grocery stores typically offer a wide range of products, including fresh produce, meat and poultry, dairy products, baked goods, canned and packaged foods, household supplies, personal care products, and more. Customers can browse products by category or search for specific items using keywords. They can add items to their virtual shopping cart, adjust quantities, and then proceed to checkout.
Delivery options also vary by store, but many offer same-day or next-day delivery in select areas, as well as scheduled delivery options for customers who prefer to plan their shopping ahead of time. Some stores also offer pickup options, where customers can place an order online and then pick it up at a designated time and location.