Review the technology options available for the log accumulation use case, compare them, and choose the right one for the modules.
- [Instructor] We will now look at existing technologies…to use to build the Server Log Accumulation pipeline.…First comes the central database,…to store the collected logs.…Let us use the same HDFS plus Hive combination…for storing server logs too.…Next, let's look at technologies to transport data…from the web servers to the final destination.…We first start with FTP,…which stands for File Transfer Protocol.…
FTP is a mature and popular technologies…that has been used extensively to move files…from one location to another.…It is simple to set up, and easy to use.…But FTP does not provide scalability out of the box.…You will have to manually set up FTP…in each of the web servers…and also perform manual consolidation…in the consolidator.…FTP, as a protocol, does not support…multiple sources and sinks.…
You will have to set up and maintain this one manually.…Regardless, it does ensure guaranteed delivery…even though it delivers file by file…and not event by event.…Next, let's consider Apache Flume.…Apache Flume is a product that was built specifically…
There is no coding involved. Instead you will see how big data tools can help solve some of the most complex challenges for businesses that generate, store, and analyze large amounts of data. The use cases are drawn from a variety of industries, including ecommerce and IT. Instructor Kumaran Ponnambalam shows how to analyze a problem, draw an architectural outline, choose the right technologies, and finalize the solution. After each use case, he reviews related best practices for data acquisition, transport, processing, storage, and service. Each lesson is rich in practical techniques and insights from a developer who has experienced the benefits and shortcomings of these technologies firsthand.
- Components of a big data application
- Big data app development strategies
- Use cases: archiving audit logs and performing customer analytics
- Technology options
- Designing solutions
- Best practices
Skill Level Advanced
Big Data Foundations: Program Managementwith Alan Simon1h 11m Intermediate
1. Intro to Big Data Applications
2. Use Case 1: Data Warehouse (DW)
3. Use Case 2: Log Accumulation (LA)
4. Use Case 3: IT Operations Analytics (OA)
5. Use Case 4: Customer 360 (C360)
6. Use Case 5: Customer Analytics (CA)
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