PANDA PV archiving. PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 1

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PANDA PV archiving PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 1

Outline - Introduction; - IFIN-HH database testbed: - before PANDA DCS core meeting (08.02.2018); - upgraded (from slide no. 20). - Outlook PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 2

PANDA DCS Architecture HESR <-> PANDA magnets -> Experiment services <-> Ext. Systems Info. Dispatcher NTP Server Monitor & Control WWW Historian Db Server Gb. Ethernet Channel Access Supervisory Layer PV Gate 1 Archiver 1 PV Gate 2 Archiver 2 PV Gate n Archiver n Control Layer I/O Controller(s) Device driver(s) I/O Controller(s) Device driver(s) I/O Controller(s) Device driver(s) DSS Interlocks bus Field Layer PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 3

PANDA DCS Architecture HESR <-> PANDA magnets -> Experiment services <-> Ext. Systems Info. Dispatcher NTP Server Monitor & Control WWW Historian Db Server Gb. Ethernet Channel Access Supervisory Layer PV Gate 1 Archiver 1 PV Gate 2 Archiver 2 PV Gate n Archiver n Control Layer I/O Controller(s) Device driver(s) I/O Controller(s) Device driver(s) I/O Controller(s) Device driver(s) DSS Interlocks bus Field Layer PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 4

IFIN-HH database testbed Firewall IPFire LAN WAN 100/1000 Mbps Switch Database server 01 Database server 02 CSS Client Supervisory Layer Cassandra PV Archiver Archiver Appliance CSS 4.4.2 IOC01 IOC02 IOC03 IOC04 IOC05 Control Layer Field Layer (PyEpics simulation script) Db Servers, CSS Client, & IOC01-03 - 2x Dual-Core AMD Opteron 2216, 8 GB RAM (Dell SC1435) Firewall, IOC03-04: Intel Xeon CPU 3.00GHz, 4 GB RAM (Dell SC1425) PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 5

IOC IOC. - EPICS 3.14.12.7 Records: Prefixes: S- sub-system, HVCh- HV channel, LVCh LV channel - record(ao,"$(s):set_hv_$(hvch)") - record(ao,"$(s):set_curr_hv_$(hvch)") - record(ai,"$(s):mon_hv_$(hvch) - record(ai,"$(s):mon_curr_hv_$(hvch)") - record(stringin,"$(s):stat_hv_$(hvch)") - record(bo,"$(s):swch_hv_$(hvch)") - record(ao,"$(s):set_lv_$(lvch)") - record(ao,"$(s):set_curr_lv_$(lvch)") - record(ai,"$(s):mon_lv_$(lvch)") - record(ai,"$(s):mon_curr_lv_$(lvch)") - record(stringin,"$(s):stat_lv_$(lvch)") - record(bo,"$(s):swch_lv_$(lvch)") - record(bo,"$(s):swch_all_hv") - record(bo,"$(s):swch_all_lv") - All ai records have ADEL, Alarm thresholds defined Substitute file: - generated with a python script where the Prefixes are set for each sub-system (sub-system name, no. of channels) PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 6

PV randomization IOC. - PyEpics 3 python module to interact with EPICS Channel Access; - Basically the script is performing three tasks in a loop: read (all) process variables generated by the ; randomize the ai records (voltage, current,.) Eq. rand_val = default_hv -11 + 2*11*random.random() default_hv = 1800 V ( record(ao,"$(s):set_hv_$(hvch)") ) field(hihi,1810) field(high,1805) field(low,1795) field(lolo,1790) field(hhsv, "MAJOR") field(hsv, "MINOR") field(lsv, "MINOR") field(llsv, "MAJOR") field(adel,5) writes the new process variables; PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 7

IOC summary IOC01 IOC02 IOC03 IOC04 IOC05 STT FTRK ECAL MVD LUMI For each sub-system - HV ch. = 1000; - LV ch. = 1000; - HV General Switch =1; - LV General Switch =1; ------------------------------- Total PV s 12.002 TOTAL 60.010 PV s PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 8

Apache Cassandra A distributed storage system for managing very large amounts of structured data spread out across many commodity servers (Avinash Lakshman, Prashant Malik 2009, Facebook) - Non-relational database management system providing high availability, no single point of failure and linear scalability; - Open source software distributed free under Apache License. Relational Database Handles moderate incoming data velocity Data arriving from one/few locations Manages primarily structured data Supports complex/nested transactions Single points of failure with failover Supports moderate data volumes Centralized deployments Data written in mostly one location Cassandra Handles high incoming data velocity Data arriving from many locations Manages all types of data Supports simple transactions No single points of failure; constant uptime Supports very high data volumes Decentralized deployments Data written in many locations PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 9

Cassandra PV Archiver Database server 01 Cassandra PV Archiver Application used to archive control systems data - ready to run in Epics based SCADA systems. Stores data in an Apache Cassandra database; Open source software available under the terms of the Eclipse Public License v1.0. Latest Release 3.2.5 (July 30th, 2017) https://oss.aquenos.com/cassandra-pv-archiver/#download Practice: Installation is very easy tested in Ubuntu 16 and CentOS 7 Well written and detailed documentation; Basic admin tasks can be performed from http://panda-dcs-server01:4812/admin/ui/; Admin via Scripts: - JSON-based archive access protocol; - requests (POST, GET) http://panda-dcs-server01:9812/archive-acess/api/1.0; Importing large no of PV can be done via xml file: - we developed a python script to generate the xml for each sub-system Performance monitoring is very poor from the /admin/ui/ - Dashboard PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 10

Cassandra PV Archiver Database server 01 Cassandra PV Archiver Raw data sample request: requests.get("http://localhost:9812/archiveaccess/api/1.0/archive/1/samples/stt:mon_lv_000?start=0&end=1528328755000 000000&prettyPrint HTTP/1.0") {"time":1518087797424860710,"severity":{"level":"minor","hasvalue":true},"statu s":"high","quality":"original","metadata":{"type":"numeric","precision":4,"units":" V","displayLow":0.0,"displayHigh":0.0,"warnLow":11.9,"warnHigh":12.1,"alarmLow" :11.8,"alarmHigh":12.2},"type":"double","value":[12.104959532825522]} PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 11

Cassandra PV Archiver Database server 01 Cassandra PV Archiver Performance monitoring - Apache Cassandra does not provide a dedicated GUI for monitoring (over time) the performance. However a metrics library is provided and this can be used to collect various node and cluster statistic data (nodetool, Jconsole not for production). - A solution based on open source software Graphite, Grafana, Apache web server and Postgres SQL was implemented on the Database server 01 (https://blog.pythian.com/monitoring-apache-cassandra-metrics-graphite-grafana/) Cassandra Server Graphite-metrics Graphite Apache web server Grafana Postgres SQL database PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 12

Cassandra performance monitoring Database server 01 Cassandra PV Archiver LiveDiskSpaceUsed MemTableLiveDataSize ReadLatency WriteLatency Unavailables Read Timeouts Read Unavailables Write Timeouts Write PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 13

Retrieving data from Cassandra Db in CS-Studio JSON Archive Proxy client plugin tool PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 14

Cassandra PV Archiver Database server 01 Cassandra PV Archiver 60.010 PV s : - Import, via.xml, takes about 50 minutes with no errors; - Archiving works but retrieval is stuck and the interface is not-responsive ; - With a single sub-system loaded (12.002 channels) I encountered no problems in the admin or retrieval of data from the Cassandra db. Single node installation shows its limits Fortunately the PV Archiver is scalable. A cluster of nodes can be implemented (hopefully with ease). I am tempted to try it soon. PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 15

Archiver Appliance Database server 02 Archiver Appliance Java based application archiver for EPICS Control systems; Developed and used at SLAC, BNL and MSU (aiming) to archive millions of PV s. https://slacmshankar.github.io/epicsarchiver_docs/details.html Practice: Installation is not simple. I used the site-specific install from https://github.com/jeonghanlee/epicsarchiverap-sites for a single production node The documentation can be better organized but is doing the job; Basic admin tasks can be performed from http://panda-dcs-server02:17665/mgmt/ui/index.html Admin via Scripts: - JSON-based archive access protocol; - requests (POST, GET) http://panda-dcs-server01:17665/mgmt/bpl/ Importing large no of PV can be done via xml file ( Channel Archiver configuration file) - we developed a python script to generate the xml for each sub-system Performance monitoring provides a lot of useful information PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 16

Archiver Appliance Metrics Database server 02 Archiver Appliance PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 17

Archiver Appliance Database server 02 Raw data sample request: Archiver Appliance - Raw data decoding utils are included in the src:./pb2json.sh /mnt/storage/arch/sts/archiverstore/stt/mon_lv_000\:2018_02_08_11.pb {"timestamp":"2018-02-08t11:59:57.412z","severity":1,"value":"12.136834570488617","status":4} - Raw data file created for each PV; - A LOT of files a single database is by far more suitable (see Cassandra) from management point of view; PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 18

Archiver Appliance Database server 02 Archiver Appliance 60.010 PV s : - Import, via.xml, took about 3 days with many start stop services and reboots. I stopped trying.; - With a single sub-system loaded (12.002 channels) I encountered no problems in the admin or retrieval of data from the raw storage. Single node installation shows its limits Fortunately the Archiver is scalable. A cluster of nodes can be implemented (hopefully with ease). I am tempted to try it soon. PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 19

IFIN-HH (upgraded) database testbed WAN Firewall/Gateway IPFire LAN 100/1000 Mbps Switch DB-SERVER01 DB-SERVER02 DB-SERVER03 CSS-CLIENT Cassandra Db Node1 Cassandra Db Node2 Cassandra Db Node3 CSS 4.4.2 192.168.1.0/24 Supervisory Layer DBGATE01 DBGATE02 DBGATE03 DBGATE04 DBGATE05 192.168.0.0/24 192.168.0.0/24 192.168.0.0/24 192.168.0.0/24 192.168.0.0/24 Control Layer STT-IOC01 FTRK-IOC01 ECAL-IOC01 MVD-IOC01 LUMI-IOC01 Field Layer (PyEpics simulation script) PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 20

IFIN-HH (upgraded) database testbed WAN Firewall/Gateway IPFire LAN 100/1000 Mbps Switch Cassandra multi-node cluster - 2 x Ubuntu 16, 1x CentOS 7 servers; - Apache Cassandra 3.11.2 DB-SERVER01 DB-SERVER02 DB-SERVER03 CSS-CLIENT Cassandra Db Node1 Cassandra Db Node2 Cassandra Db Node3 CSS 4.4.2 192.168.1.0/24 Supervisory Layer DBGATE01 DBGATE02 DBGATE03 DBGATE04 DBGATE05 192.168.0.0/24 192.168.0.0/24 192.168.0.0/24 192.168.0.0/24 192.168.0.0/24 Control Layer STT-IOC01 FTRK-IOC01 ECAL-IOC01 MVD-IOC01 LUMI-IOC01 Field Layer (PyEpics simulation script) PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 21

IFIN-HH (upgraded) database testbed WAN Firewall/Gateway IPFire LAN 100/1000 Mbps Switch Cassandra PV Archivers - 5 x CentOS 7 servers; - Cassandra PV Archiver 3.2.5; DB-SERVER01 DB-SERVER02 DB-SERVER03 CSS-CLIENT Cassandra Db Node1 Cassandra Db Node2 Cassandra Db Node3 CSS 4.4.2 192.168.1.0/24 Supervisory Layer DBGATE01 DBGATE02 DBGATE03 DBGATE04 DBGATE05 192.168.0.0/24 192.168.0.0/24 192.168.0.0/24 192.168.0.0/24 192.168.0.0/24 Control Layer STT-IOC01 FTRK-IOC01 ECAL-IOC01 MVD-IOC01 LUMI-IOC01 Field Layer (PyEpics simulation script) PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 22

IFIN-HH (upgraded) database testbed WAN Firewall/Gateway IPFire LAN 100/1000 Mbps Switch Cassandra PV Archivers - 5 x CentOS 7 servers; - Cassandra PV Archiver 3.2.5; DB-SERVER01 DB-SERVER02 DB-SERVER03 CSS-CLIENT Cassandra Db Node1 Cassandra Db Node2 Cassandra Db Node3 CSS 4.4.2 192.168.1.0/24 Supervisory Layer DBGATE01 DBGATE02 DBGATE03 DBGATE04 DBGATE05 192.168.0.0/24 192.168.0.0/24 192.168.0.0/24 192.168.0.0/24 192.168.0.0/24 Control Layer STT-IOC01 FTRK-IOC01 ECAL-IOC01 MVD-IOC01 LUMI-IOC01 Field Layer (PyEpics simulation script) PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 23

IFIN-HH (upgraded) database testbed Cassandra Performance monitoring - We switched from Graphite to Prometheus; - jmx-exporter: java agent which exports local JVM metrics as Prometheus metrics; DB-SERVER01 DB-SERVER02 DB-SERVER03 CSS-CLIENT Cassandra Db Node1 Cassandra Db Node2 Cassandra Db Node3 CSS 4.4.2 jmx-exporter node-exporter jmx-exporter node-exporter jmx-exporter node-exporter Prometheus 2.2 Grafana 5.0 Supervisory Layer 192.168.1.0/24 DBGATE01 DBGATE02 DBGATE03 DBGATE04 DBGATE05 node-exporter node-exporter node-exporter node-exporter node-exporter Control Layer PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 24

IFIN-HH (upgraded) database testbed General Performance monitoring - Node-exporter: exports machine hardware and OS metrics to Prometheus; - Grafana dashboard to monitor CPU, RAM, HDD,... DB-SERVER01 DB-SERVER02 DB-SERVER03 CSS-CLIENT Cassandra Db Node1 Cassandra Db Node2 Cassandra Db Node3 CSS 4.4.2 jmx-exporter node-exporter jmx-exporter node-exporter jmx-exporter node-exporter Prometheus 2.2 Grafana 5.0 Supervisory Layer 192.168.1.0/24 DBGATE01 DBGATE02 DBGATE03 DBGATE04 DBGATE05 node-exporter node-exporter node-exporter node-exporter node-exporter Control Layer PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 25

IFIN-HH database testbed Performance Monitoring PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 26

IFIN-HH database testbed Cassandra Monitoring PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 27

IFIN-HH database testbed Hardware Monitoring PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 28

IFIN-HH database testbed Hardware Monitoring PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 29

CSS Data Browser retrieving from Cassandra database CSS4 repo: http://panda-repo.gsi.de/mario/controlsystemstudio.git - 5 PV s ( 1 / sub-system) 5 days history (no failures in the IOC and/or Python Epics scripts ) PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 30

Custom code to query the Cassandra database Based on Datastax Cassandra drivers (C/C++, C#, Java, Node.js, Python, and Ruby) The drivers can be used to send CQL statements from client Cassandra cluster; The tool is very powerful: retrieve, manipulate or remove data; Python script to retrieve PV in a given time interval is ready; Output: STT:MON_HV_123 1520295168766427826 channel_access_scalar_double(value=1809.2962690444097, alarm_severity=1, alarm_status=4, precision=2, units=u'v', lower_warning_limit=1795.0, upper_warning_limit=1805.0, lower_alarm_limit=1790.0, upper_alarm_limit=1810.0, lower_display_limit=0.0, upper_display_limit=0.0, lower_control_limit=0.0, upper_control_limit=0.0) Usage of GnuPlot for PV visualization is under development. PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 31

PV archiving hints from EPICS community Spring 2017 EPICS Collaboration Meeting, Kyoto University PANDA Collaboration Meeting 18/1, Alexandru Mario Bragadireanu, Particle Physics Department, IFIN-HH Măgurele 32

Summary and Outlook Controls TDR preparation is moving ahead. - the scheme with (at least) one archiver machine / sub-system and a dedicated database cluster looks feasible. Some more work is needed for: - The evaluation of overall controls data throughput, storage and retrieval; - Detector Safety System; - Hardware proof of concept (dedicated meeting scheduled for 08.03 @ 14:30 ).