Search Results for "zabbix-sql-scripts"

...It provides syntax‐highlighting, multiline editing, auto‐completion, and dynamic importing of dependencies (using a magic import syntax like import $ivy…). Instead of having to set up an sbt project for many small tasks, one can write Scala scripts (with .sc extension) and run them directly, with Ammonite handling compilation and execution transparently. In the REPL, Ammonite can survive compiler errors (by restarting the compiler internally) and preserve session state, improving resilience compared to the default Scala REPL. It also integrates filesystem utilities and command-line abstractions (via Ammonite-Ops) so that common shell tasks become more Scala-native.

ScalikeJDBC is a tidy SQL-based DB access library for Scala developers. This library naturally wraps JDBC APIs and provides you easy-to-use and very flexible APIs. What’s more, QueryDSL makes your code type-safe and reusable. ScalikeJDBC is a practical and production-ready one. Use this library for your real projects. Whether you like it or not, JDBC is a stable standard interface.

Apache Spark is a unified engine for large-scale data processing, offering APIs for batch jobs, streaming, machine learning, and graph computation. It builds on resilient distributed datasets (RDDs) and the newer DataFrame/Dataset abstractions to provide fault-tolerant, in-memory computation across clusters. Spark’s execution engine handles scheduling, shuffles, caching, and data locality so users can focus on transformations rather than infrastructure plumbing. With Spark Streaming...

Gatling is a high-performance load testing tool built on the JVM that emphasizes realism, scalability, and developer ergonomics. Test scenarios are scripted in a concise Scala-based DSL, allowing you to model user journeys with think times, feeders (dynamic data), checks, and assertions all in code. Its asynchronous, non-blocking engine (backed by Netty) can drive very high concurrency from a single injector, reducing the need for large injector farms. Gatling supports HTTP out of the box as...

...By writing your queries in Scala you can benefit from the static type checking, compile-time safety, and compositionality of Scala, while retaining the ability to drop down to raw SQL where needed for custom or advanced database features.

...The project invests heavily in verification: differential testing against reference models, extensive random instruction tests, and full software stacks (bootloaders, Linux) to validate correctness under realistic workloads. Tooling around the core (build scripts, simulators, waveform/debug support) lowers the barrier for academics and industry contributors to experiment and extend.

...Rather than requiring every application to embed Spark or manage Spark contexts manually, this server abstracts a long-lived service where clients can upload JARs, start and stop contexts, submit jobs synchronously or asynchronously, and manage named objects (RDDs / DataFrames) across job executions. It supports multiple modes (transient jobs, persistent contexts for reuse, streaming, SQL/Hive, etc.), and can be integrated with authentication/authorization systems (e.g. via Apache Shiro). The architecture isolates Spark contexts (optionally in separate JVMs), isolates job dependencies, and persists job / jar metadata via pluggable DAOs. It supports deployment across cluster managers (YARN, Mesos, etc.) and aims to simplify Spark-as-a-service scenarios.

HiveMind is a browser based web development that combines an application container (jetty), a middleware and a developer environment that runs in the browser. It runs on the jvm so you are not limited by environment. You can run it on your laptop, company server or even on a cloud service like AWS. It supports Java, Ruby, Python, JavaScript, Groovy, Clojure. Source include so it is easy to hack so you can modify it for your own need.

Gizzard is a Scala framework originally developed by Twitter for building scalable, fault-tolerant, distributed key-value stores that can be sharded and replicated. It provides infrastructure for routing requests through shard trees, splitting or rebalancing shards dynamically, failover, and migrations. In Gizzard, data is stored in underlying storage shards (which could be databases or other stores) and Gizzard handles the process of routing requests correctly as the cluster topology...