Ops Center Analyzer Detail View REST API Reference Guide

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The Hitachi Ops Center Analyzer detail view (Analyzer detail view) database is a high-performance, size-optimized, and NoSQL database that offers highly efficient storage and retrieval capabilities. It can store time series data at a high granularity, including minute-level data for a long period. You can query this data using an expressive and powerful yet concise query language (MQL). MQL is uniquely designed, which makes it different from the commonly used Structured Query Language (SQL).

The Analyzer detail view REST API allows you to build an application around the Analyzer detail view database.

The API functions of Analyzer detail view conform to the REST (Representational State Transfer) architecture.

The API requests are handled by the API server, which in turn passes them to the Analyzer detail view database through the CRUD backend (Create, Retrieve, Update, and Delete, the common database operations backend). The CRUD backend uses resource management techniques to efficiently route and process multiple API requests.

The Analyzer probe server collects the data and stores it in the Analyzer detail view database. You can also store the data in the Analyzer detail view database using the third-party application.

The following diagram shows the architecture of the Analyzer detail view REST API server.

The Analyzer detail view REST API architecture consists of the following:

  • Analyzer detail view REST API This interface is powered by the Jetty web server and is responsible for accepting incoming HTTP requests, parsing and passing them to the Analyzer detail view CRUD interface.
  • Analyzer detail view CRUD interface This interface accepts each request from the REST API and adds it to an in-memory waiting queue.
  • Scheduler Continuously monitors the waiting queue and moves runnable requests to the running queue. The scheduler decides on runnable requests among all the waiting requests on the basis of request-level locks. The running queue is bounded by the in-memory queue and its size is equal to the number of threads configured in the request processor.
  • Multi-threaded request processor Instead of processing each API request on a separate thread, which can be inefficient on resources, the multi-threaded request processor uses the pool of worker threads to throttle the API requests processing.

    The number of worker threads can be tuned to process requests in parallel. Each request from a running queue is picked up by a worker thread. The request processor interacts with the underlying database.

  • Analyzer detail view database Consists of schema and data. The schema consists of attribute and resource definitions, whereas the data is of two types: scalar and time series. The Analyzer detail view database has a separate store for schema, scalar, and time series data in the Analyzer detail view virtual file system.

    The schema is stored in an unbounded cache. The scalar data is stored in a bounded cache up to a maximum of 1000 elements, where an element is an index of stored scalar value. The least recently used (LRU) policy is used to delete elements from the scalar data cache.

    You can view the schema in the Analyzer detail view GUI.