ESA Science Archives Architecture Evolution. Iñaki Ortiz de Landaluce Science Archives Team 13 th Sept 2013
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1 ESA Science Archives Architecture Evolution Iñaki Ortiz de Landaluce Science Archives Team 13 th Sept 2013
2 Outline Introduction: ESA Science Archives Archives Architecture Evolution User Interfaces and the Web 2.0 Application Frameworks Databases, Spatial Indexing and Big Data Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 2
3 Outline Introduction: ESA Science Archives Archives Architecture Evolution User Interfaces and the Web 2.0 Application Frameworks Databases, Spatial Indexing and Big Data Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 3
4 ESAC Science Archives Strategy Large set of science archives co-located at ESAC are a major research asset for community. Need to be kept readily available for future users and novel uses. Thus, must plan now for next years. Planning based around 3 major goals: Enable maximum scientific exploitation of data sets, Enable efficient long-term preservation of data, software and knowledge, using modern technology Enable cost-effective archive production by integration in, and across, projects.
5 Introduction: ESA Science Archives Different types of Missions: Astronomy, Planetary, Solar System, Data: Raw data, calibrated processed data, high level data products, Users: Scientific Community (public access) PI team and observers (controlled access) Science Operations Team (privileged access) Common Architecture and Look and Feel Better corporate image for ESA Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 24th May 2013 Pag. 5
6 ESA Science Archives - Astronomy Euclid 2005 Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 6
7 ESA Science Archives Planetary & Solar System Solar Orbiter Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 7
8 ESA Science Archives - Mission Phases Support ESA Science Archives support missions in different phases Development Operations (EOP, CP, PVP, SDP, RP ) Post-operations and Legacy Archive Early start of archiving activities within the mission phases Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 8
9 Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 9
10 Outline Introduction: ESA Science Archives Archives Architecture Evolution User interfaces and the Web 2.0 Application Frameworks Databases, Spatial Indexing and Big Data Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 10
11 ESA Science Archives Architecture Evolution Technology has evolved enormously since Also, new and heterogeneous requirements had to be addressed: Different mission types: multi-wavelength astronomy, solar and planetary Increasing number of archives New network and security policies That resulted into 3 different generation of archives: ISO Data Archive INTEGRAL Science Data Archive Planetary Science Archive MEX VEX ROSETTA HUYGENS and others SOHO Science Archive EXOSAT Science Archive Planck Legacy Archive Herschel Science Archive Cluster Ulysses Final Archive XMM-Newton Science Archive ESA Hubble Science Archive Euclid GAIA Solar Orbiter Bepi Colombo Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 11
12 Outline Introduction: ESA Science Archives Archives Architecture Evolution User Interfaces and the Web 2.0 Application Frameworks Databases, Spatial Indexing and Big Data Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 12
13 User Interfaces and Web 2.0 Year 1998: First generation of ESA Science Archives (ISO) HTML 3, Netscape and IE Web could not satisfy user requirements visualization dynamic content Small and dynamic applications could run from a browser using plug-ins Flash, Java Applets 2006: Second generation of ESA Science Archives (SOHO, EXOSAT,..) Java Applets replaced by Java Web Start Technology (JNLP) Desktop application Java Version updating and Pack200 compression Security enhancements Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 13
14 User Interfaces and Web 2.0 The web revolution: From Dot-com to Web 2.0 and beyond Fully-featured dynamic contents (HTML5, CSS3, AJAX) Video and Audio support No plug-ins required 2D/3D Graphics Rendering (WebGL) Ubiquity, The Web becomes social Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 14
15 User Interfaces and Web 2.0 Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 15
16 User Interfaces and Web : Third generation of archives kick-off Feasibility study to implement Web-based Archive User Interfaces Web-based technologies assessment Impact on current ESA Archives Architecture SWOT Analysis Analysis of existing web-based archives: HEASARC, CDS ASDC, ISDC, Spitzer, Hubble, CADC, ESO, PDS, SDSS GWT is the selected technology Small learning curve for Java developers Long Term Support expected (it s Google) Wide community 2013: Release of first web-based ESA Science Archives Ulysses Final Archive XMM-Newton Science Archive Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 16
17 User Interfaces Evolution 1 st Generation 2nd Generation 3rd Generation In Progress Java Applet Java Web Start Web based WebGL Java 1.1+ Abstract Window Toolkit Java 1.5+ Java Swing, JGoodies Enhanced visualization tools In-house RPC connection through TCP/IP HTTP Inter-operability Inter-operability (Web Profile) Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 17
18 User Interfaces - 1 st Generation of ESA Science Archives Applets Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 18
19 User Interfaces 2 nd Generation of ESA Science Archives Java Web Start Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 19
20 User Interfaces 3 rd Generation of ESA Science Archives Web applications Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 20
21 Outline Introduction: ESA Science Archives Archives Architecture Evolution User Interfaces and the Web 2.0 Application Frameworks Databases, Spatial Indexing and Big Data Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 21
22 Application Frameworks 1 st Generation 2nd Generation 3rd Generation In Progress In-house developed java server in non standard ports Single software in servlet container High availability In-house RPC connection through TCP/IP HTTP Load balancing In-house developed load balancing Use of standard ports and protocols + VO compatible interfaces (TAP, VOSpace) File retrieval through port 21 File retrieval through port 80 VO data access protocols (SIAP, SSAP, SLAP) Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 22
23 Outline Introduction: ESA Science Archives Archives Architecture Evolution User Interfaces and the Web 2.0 Application Frameworks Databases, Spatial Indexing and Big Data Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 23
24 Databases 1 st Generation 2 nd Generation 3 rd Generation (In Progress) JDBC Access In-house developed connection pooling Standard connection pooling (c3p0) High Availability Non standard, ad-hoc pagination Standard Pagination (Hibernate + Postgresql) Spatial indexing (q3c, h3c, pgsphere) Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 24
25 Spatial Indexing Allows better performance on complex geometrical queries Cone-Search, X-Match Complex FOV overlap operations Avoids squaring ROI and post-processing overhead Some Sky-Pixelation schemas HEALPix: Hierarchical Equal Area Iso Latitude HTM: Hierarchical Triangular Mesh Q3C: Quad Tree Cube PostgreSQL Plug-ins: PgSphere, Q3C and H3C (HEALPix + Q3C) Database manages Geometrical operators and shapes FOVs of stored observations are pre-computed Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 25
26 Spatial Indexing Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 26
27 Spatial Indexing Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 27
28 Spatial Indexing Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 28
29 Spatial Indexing Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 29
30 Spatial Indexing Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 30
31 Big Data ESA Science Archive data volume increasing exponentially Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 31
32 Big Data ESA Science Archive data volume increasing exponentially GAIA: 1 billion sources GUMS catalogue (synthetic) ~2 billion sources Map-Reduce paradigm applied to PostgreSQL RDBMS Hadoop cluster for advanced applications Some numbers Positional + Magnitude X-Match GUMS Stellar Sources Catalogue ~2 billion sources Fuzzy Synthetic Catalogue ~100 million sources 1 degree radius, 9 seconds Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 32
33 Big Data ESA Science Archive data volume increasing exponentially GAIA: 1 billion sources GUMS catalogue (synthetic) ~2 billion sources Map-Reduce paradigm applied to PostgreSQL RDBMS Hadoop cluster for advanced applications Some numbers Positional + Magnitude X-Match GUMS Stellar Sources Catalogue ~2 billion sources Fuzzy Synthetic Catalogue ~100 million sources 1 degree radius, 9 seconds H-R Diagram, Full GUMS catalogue 30 minutes Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 33
34 Big Data ESA Science Archive data volume increasing exponentially GAIA: 1 billion sources GUMS catalogue (synthetic) ~2 billion sources Map-Reduce paradigm applied to PostgreSQL RDBMS Hadoop cluster for advanced applications Some numbers Positional + Magnitude X-Match GUMS Stellar Sources Catalogue ~2 billion sources Fuzzy Synthetic Catalogue ~100 million sources 1 degree radius, 9 seconds H-R Diagram, Full GUMS catalogue 30 minutes Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 34
35 Big Data Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 35
36 Come and visit us Science Archives Architecture Evolution Iñaki Ortiz de Landaluce ESAC 13th Sept 2013 Pag. 36
37 THANK YOU Science Archives Architecture Evolution
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