Antonio Pierro

Persistent storage of non-event data in the CMS databases

In the CMS experiment, the non event data needed to set up the detector, or being produced by it, and needed to calibrate the physical responses of the detector itself are stored in ORACLE databases. The large amount of data to be stored, the number of clients involved and the performance requirements make the database system an essential service for the experiment to run. This note describes the CMS condition database architecture, the data-flow and PopCon, the tool built in order to populate the offline databases. Finally, the first experience obtained during the 2008 and 2009 cosmic data taking are presented.

SQL-jQuery client a tool managing the DB backend of the CMS software framework through Web Browser

PJ-SQL-Browser is a free Python-Javascript web-based tool. It relies on jQuery and python libraries, and is intended to provide the CMS software framework a real-time handle to the DB backend inside a local web browser.

First experience in operating the population of the condition databases for the CMS experiment

Reliable population of the condition databases is critical for the correct operation of the online selection as well as of the offline reconstruction and analysis of data. We will describe here the system put in place in the CMS experiment to populate the database and make condition data promptly available both online for the high-level trigger and offline for reconstruction. The system, designed for high flexibility to cope with very different data sources, uses POOL-ORA technology in order to store data in an object format that best matches the object oriented paradigm for C++ programming language used in the CMS offline software. In order to ensure consistency among the various subdetectors, a dedicated package, PopCon (Populator of Condition Objects), is used to store data online. The data are then automatically streamed to the offline database hence immediately accessible offline worldwide. This mechanism was intensively used during 2008 in the test-runs with cosmic rays. The experience of this first months of operation will be discussed in detail.

CMS conditions database web application service

The web application service is part of the condition database system of the CMS experiment. The application server is built upon condition python API in the CMS offline software framework and serves applications and users not involved in the event-processing. The main client of the application server is the condition database web GUI, which currently exposes three main services: the Tag Browser, the Global Tag, the Historic Chart condition date in terms of their version (TAG) and the interval of validity (IOV). The global tag component is used by physicists to inspect the organization of the tags in a given data taking or data production, while production managers use the web service to produce such tag hierarchy. The History chart plotting service creates dynamic summary and distribution charts of the payload data in the database. Fast graphical overview of different information greatly contributes in monitoring and validating the calibration data stored in the condition database.

Probing methods for automatic error resolution in a heterogeneous software environment

We investigate the feasibility to improve the error resolution through automation like natural language-based and statistical analysis algorithms, in order to detect errors and security issues, and to convert error messages from encrypted into human-readable ones in a heterogonous software environment. To reach this goal we study a real case using the data extracted from PopCon, a package used for the population of CMS Condition Databases, that is embedded into CMS Software framework, CMSSW, and relies on different underlying applications such as ORACLE, POOL, CORAL in order to perform database transactions.

Real time monitoring system for applications performing the population of condition databases for CMS non-event data

In real time systems, such as CMS Online Condition Database, monitoring and fast detecting errors is a very challenging task. To recover the system and to put it in a safe state requires spotting a faulty situation with strict timing constraints and a fast reaction.