This document discusses messaging queues and platforms. It begins with an introduction to messaging queues and their core components. It then provides a table comparing 8 popular open source messaging platforms: Apache Kafka, ActiveMQ, RabbitMQ, NATS, NSQ, Redis, ZeroMQ, and Nanomsg. The document discusses using Apache Kafka for streaming and integration with Google Pub/Sub, Dataflow, and BigQuery. It also covers benchmark testing of these platforms, comparing throughput and latency. Finally, it emphasizes that messaging queues can help applications by allowing producers and consumers to communicate asynchronously.
The document discusses Amazon Web Services (AWS) Batch and how it can help customers run batch computing workloads on AWS. It notes that AWS Batch automatically provisions the optimal quantity and type of compute resources (e.g., EC2 instances) required to run jobs efficiently. It also allows customers to integrate their own scheduling and application code with AWS Batch through simple API calls or SDKs.
AWS Japan YouTube 公式チャンネルでライブ配信された 2022年4月26日の AWS Developer Live Show 「Infrastructure as Code 談議 2022」 の資料となります。 当日の配信はこちら からご確認いただけます。
https://youtu.be/ed35fEbpyIE
The document discusses Amazon Web Services (AWS) Batch and how it can help customers run batch computing workloads on AWS. It notes that AWS Batch automatically provisions the optimal quantity and type of compute resources (e.g., EC2 instances) required to run jobs efficiently. It also allows customers to integrate their own scheduling and application code with AWS Batch through simple API calls or SDKs.
AWS Japan YouTube 公式チャンネルでライブ配信された 2022年4月26日の AWS Developer Live Show 「Infrastructure as Code 談議 2022」 の資料となります。 当日の配信はこちら からご確認いただけます。
https://youtu.be/ed35fEbpyIE
This document contains code snippets in Python for analyzing stock market data, normalizing features, performing grid search for an SVM classifier, and using the classifier to make predictions and tweet the results. The snippets load CSV data, sort values by date, normalize features, tune an SVM using grid search, make predictions, and tweet the prediction using the Twitter API.
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