Critical Description
Synopsis
The current Apache Wayang (Incubating) approach to communicate to different platforms uses a Channel abstraction. The idea behind a channel is to generate a source and sink operator in the platform that enables the communication between two platforms. Yet, the currency approach does not handle any possible bottleneck that could be created at the target platform (sink operator). For example, when moving data from Apache Spark to PostgreSQL we could expect a bottleneck at the PostgreSQL if the incoming is big: distributed platform vs a single-node platform. This of course will generate problems at the PostgreSQL side or would even cause data losses. We thus aim at poewring communication channels with Apache Kafka support, where a queue can make the data movement between platforms more smoothly.
Benefits to Community
The community benefit will be the utilization of Apache Kafka as a channel of communication. This will be helping in adding speed to the processing of the queries and provide a better setup and more alternatives for the optimizer.
Deliverables
The delivery expected is to add a robust solution for the inclusion of the Apache Kafka as a Channel of communication.
The step expected are the following:
- Understand the paper [1]
- Get into the internals of the communication channels of Apache Wayang (Incubating)
- Discuss and design the solution for the loop optimizations
- Implement and integrate the new Channel communications inside Apache Wayang (Incubating).
Related Work
[1] [RHEEMix in the data jungle: a cost-based optimizer for cross-platform systems](https://wayang.apache.org/assets/pdf/paper/journal_vldb.pdf)
Biographical Information of the possible mentors
Bertty Contreras-Rojas is a Senior Software Engineer at Databloom Inc. He is one of the PPMC of Apache Wayang(Incubating). He has many years of experience developing intensive processing data systems for several industries, such as banking systems. He was a research engineer at the Qatar Computing Research Institute, where he was responsible for developing the declarative query engine for Rheem and adding new underlying platforms to Rheem.
Rodrigo Pardo-Meza is a Senior Software Engineer at Databloom Inc. He is one of the PPMC of Apache Wayang(Incubating). He has many years of experience developing applications that support Big Data processing, with experience implementing ETL processes over distributed systems to optimize inventories in supply chains. He was a research engineer at the Qatar Computing Research Institute, where he specialized in human interface interaction with big data analytics. During this time, he co-develop an ML-based cross-platform query optimizer.
Jorge Quiané is the head of the Big Data Systems research group at the Berlin Institute for the Foundations of Learning and Data (BIFOLD) and a Principal Researcher at DIMA (TU Berlin). He also acts as the Scientific Coordinator of the IAM group at the German Research Center for ArtificialIntelligence (DFKI). His current research is in the broad area of big data: mainly in federated data analytics, scalable data infrastructures, and distributed query processing. He has published numerous research papers on data management and novel system architectures. He has recently been honoured with the 2022 ACM SIGMOD Research Highlight Award and the Best Paper Award at ICDE 2021 for his work on “EfficientControl Flow in Dataflow Systems”. He holds five patents in core database areas and on machine learning. Earlier in his career, he was a Senior Scientist at the Qatar Computing Research Institute (QCRI) and a Postdoctoral Researcher at Saarland University. He obtained his PhD in computer science from INRIA (Nantes University).
Name and Contact Information
Name: Bertty Contreras-Rojas
email: bertty (at) apache.org
community: dev (at) wayang.apache.org
website: https://wayang.apache.org
