Search Results for "spark"

Apache Sedona™ is a cluster computing system for processing large-scale spatial data. Sedona extends existing cluster computing systems, such as Apache Spark and Apache Flink, with a set of out-of-the-box distributed Spatial Datasets and Spatial SQL that efficiently load, process, and analyze large-scale spatial data across machines. According to our benchmark and third-party research papers, Sedona runs 2X - 10X faster than other Spark-based geospatial data systems on computation-intensive query workloads. ...

The AWS Serverless Java Container library is a framework that allows developers to run existing or new Java web applications—built with frameworks such as Spring, Jersey, Spark, Struts—inside AWS Lambda with minimal modifications. It bridges the gap between traditional servlet or web-framework models and serverless functions by mapping HTTP events from API Gateway into requests your framework understands and routing responses back appropriately. This means you can keep much of your familiar Java-based architecture (controllers, filters, dependency injection) and deploy it in a serverless environment without rewriting everything from scratch. ...

Soot is a Java optimization framework. It provides four intermediate representations for analyzing and transforming Java bytecode. Baf: a streamlined representation of bytecode which is simple to manipulate. Jimple: a typed 3-address intermediate representation suitable for optimization. Shimple: an SSA variation of Jimple. Grimp: an aggregated version of Jimple suitable for decompilation and code inspection.

Apache Beam is an open source, unified programming model to define both batch and streaming data-parallel processing pipelines, as well as certain language-specific SDKs for constructing pipelines and Runners. These pipelines are executed on one of Beam’s supported distributed processing back-ends, which include Apache Apex, Apache Flink, Apache Spark, and Google Cloud Dataflow. Beam is especially useful for Embarrassingly Parallel data processing tasks, and caters to the different needs and backgrounds of end users, SDK writers and runner writers.