Amazon EMR
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Google Cloud Dataflow
Google Cloud Dataproc
Databricks
Qubole
Snowflake
HortonWorks Data Platform
Google Site Reliability Engineering
Ganeti
Apache Helix
Linux Foundation Training
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Based on our record, Google Site Reliability Engineering should be more popular than Amazon EMR. It has been mentiond 84 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
There are different ways to implement parallel dataflows, such as using parallel data processing frameworks like Apache Hadoop, Apache Spark, and Apache Flink, or using cloud-based services like Amazon EMR and Google Cloud Dataflow. It is also possible to use parallel dataflow frameworks to handle big data and distributed computing, like Apache Nifi and Apache Kafka. Source: about 1 year ago
I'm going to guess you want something like EMR. Which can take large data sets segment it across multiple executors and coalesce the data back into a final dataset. Source: almost 2 years ago
This is exactly the kind of workload EMR was made for, you can even run it serverless nowadays. Athena might be a viable option as well. Source: almost 2 years ago
Apache Spark is one of the most actively developed open-source projects in big data. The following code examples require that you have Spark set up and can execute Python code using the PySpark library. The examples also require that you have your data in Amazon S3 (Simple Storage Service). All this is set up on AWS EMR (Elastic MapReduce). - Source: dev.to / over 2 years ago
Check out https://aws.amazon.com/emr/. Source: about 2 years ago
In my view it is having a dedicated team focusing their full mental bandwidth on pro-actively understanding and managing robustness of the system. In Pure DevOps, it seems to me developers often don't have the full picture of the system, and not enough bandwidth to foresee complex interactions from their changes. These are from my experiences spending one year as a developer in somewhat large a greenfield... - Source: Hacker News / 6 months ago
Site Reliability Engineering, introduced by Google, extends the principles of software engineering to operations. Unlike DevOps, SRE places a stronger emphasis on reliability, availability, and scalability. SRE teams are tasked with maintaining the health and performance of systems by applying engineering practices to operations. The ultimate objective is to achieve a balance between service reliability and... Source: 9 months ago
Define SLOs for availability and latency. Google's SRE book is good reading for this. Source: 11 months ago
Have you gone through the SRE Books? Source: 11 months ago
Google SRE books is always a good read. Source: 12 months ago
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Ganeti - Ganeti is a cluster management tool built on top of existing virtualization technologies.
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
Apache Helix - A cluster management framework for partitioned and replicated distributed resources
Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
Linux Foundation Training - Linux Foundation Training is a complete web-based platform that offers you advanced-level and updated courses and tutorials to learn the developing and programming skills.