Modern scientific experiments collect vast amounts of data that must be catalogued to meet multiple use cases and search criteria. In particular, high-energy physics experiments currently in ...operation produce several billion events per year. A database with the references to the files including each event in every stage of processing is necessary in order to retrieve the selected events from data storage systems. The ATLAS EventIndex project is studying the best way to store the necessary information using modern data storage technologies (Hadoop, HBase etc.) that allow saving in memory key-value pairs and select the best tools to support this application from the point of view of performance, robustness and ease of use. This paper describes the initial design and performance tests and the project evolution towards deployment and operation during 2014.
The EventIndex is the complete catalogue of all ATLAS events, keeping the references to all files that contain a given event in any processing stage. It replaces the TAG database, which had been in ...use during LHC Run 1. For each event it contains its identifiers, the trigger pattern and the GUIDs of the files containing it. Major use cases are event picking, feeding the Event Service used on some production sites, and technical checks of the completion and consistency of processing campaigns. The system design is highly modular so that its components (data collection system, storage system based on Hadoop, query web service and interfaces to other ATLAS systems) could be developed separately and in parallel during LSI. The EventIndex is in operation for the start of LHC Run 2. This paper describes the high-level system architecture, the technical design choices and the deployment process and issues. The performance of the data collection and storage systems, as well as the query services, are also reported.
The EventIndex is the complete catalogue of all ATLAS real and simulated events, keeping the references to all permanent files that contain a given event in any processing stage; its implementation ...has been substantially revised in advance of LHC Run 3 to be able to scale to the higher production rates. The Event Picking Server automates the procedure of finding the locations of large numbers of events, extracting and collecting them into separate files. It supports different formats of events and has an elastic workflow for different input data. The convenient graphical interface of the Event Picking Server is integrated with ATLAS SSO. The monitoring system controls the performance of all parts of the service.
The ATLAS Eventlndex is the global catalogue of all ATLAS real and simulated events. During the LHC long shutdown between Run 2 (20152018) and Run 3 (2022-2025) all its components were substantially ...revised and a new system was deployed for the start of Run 3 in Spring 2022. The new core storage system, based on HBase tables with a SQL interface provided by Phoenix, allows much faster data ingestion rates and scales much better than the old one to the data rates expected for the end of Run 3 and beyond. All user interfaces were also revised and a new command-line interface and web services were also deployed. The new system was initially populated with all existing data relative to Run 1 and Run 2 datasets, and then put online to receive Run 3 data in real time. After extensive testing, the old system, which ran in parallel to the new one for a few months, was finally switched off in October 2022. This paper describes the new system, the move of all existing data from the old to the new storage schemas and the operational experience gathered so far.
The ATLAS EventIndex for LHC Run 3 Barberis, Dario; Aleksandrov, Igor; Alexandrov, Evgeny ...
EPJ Web of Conferences,
01/2020, Letnik:
245
Journal Article, Conference Proceeding
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Odprti dostop
The ATLAS EventIndex was designed in 2012-2013 to provide a global event catalogue and limited event-level metadata for ATLAS analysis groups and users during the LHC Run 2 (2015-2018). It provides a ...good and reliable service for the initial use cases (mainly event picking) and several additional ones, such as production consistency checks, duplicate event detection and measurements of the overlaps of trigger chains and derivation datasets. The LHC Run 3, starting in 2021, will see increased data-taking and simulation production rates, with which the current infrastructure would still cope but may be stretched to its limits by the end of Run 3. This proceeding describes the implementation of a new core storage service that will be able to provide at least the same functionality as the current one for increased data ingestion and search rates, and with increasing volumes of stored data. It is based on a set of HBase tables, with schemas derived from the current Oracle implementation, coupled to Apache Phoenix for data access; in this way we will add to the advantages of a BigData based storage system the possibility of SQL as well as NoSQL data access, allowing to re-use most of the existing code for metadata integration.
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