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SimDB and SimTAP Dealing with a complex data model Gerard Lemson, Nara, 2010-12-10
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SimDB and SimDAL Protocols to support describing simulations –Simulation Data Model: Model for N-body 3+1D any simulations http://volute.googlecode.com/svn/trunk/projects/theory/snapdm/specification/uml/SimDB_DM.png http://volute.googlecode.com/svn/trunk/projects/theory/snapdm/specification/uml/SimDB_DM.png publishing simulations –Simulation Database (SimDB): protocol for accessing a database built according to SimDM. finding simulations –SimDB/TAP –queryData in SimDAL –SimTAP retrieving simulation data, whole, in parts, manipulated –SimDAL getData services (not in this talk) Btw: simulation can be –simulation run –simulation result –simulation data –post-processing of simulation results
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SimDB/REST simple access to SimDB Uses XML representation of model –XML schema http://code.google.com/p/volute/source/browse/#svn/trunk/projects/theory/snapdm/specification/xsd http://code.google.com/p/volute/source/browse/#svn/trunk/projects/theory/snapdm/specification/xsd Examples http://code.google.com/p/volute/source/browse/#svn/trunk/projects/theory/snapdm/specification/examples http://code.google.com/p/volute/source/browse/#svn/trunk/projects/theory/snapdm/specification/examples –PDR http://code.google.com/p/volute/source/browse/#svn/trunk/projects/theory/snapdm/specification/examples/external/PDR http://code.google.com/p/volute/source/browse/#svn/trunk/projects/theory/snapdm/specification/examples/external/PDR –Gadget2 http://volute.googlecode.com/svn-history/r1382/trunk/projects/theory/snapdm/specification/examples/external/Gadget2/Gadget2.xml http://volute.googlecode.com/svn-history/r1382/trunk/projects/theory/snapdm/specification/examples/external/Gadget2/Gadget2.xml –TODO more (SVO) VO-URP –validator http://www.g-vo.org/SimDB-browser/Validate.do http://www.g-vo.org/SimDB-browser/Validate.do –upload http://www.g-vo.org/SimDB-browser http://www.g-vo.org/SimDB-browser –download http://www.g-vo.org/SimDB-browser http://www.g-vo.org/SimDB-browser
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SimDB/TAP Model complex –Too(?) complex for trivial (parameter based) query language –Need special navigation tools (vo-urp@gavo)vo-urp@gavo –Need powerful query language Impement TAP on database built according to SimDM Map UML to RDB model –TAP_SCHEMA for SimDM (vo-urp@gavo old) http://code.google.com/p/volute/source/browse/#svn/trunk/projects/theory/snapdm/specification/tapvo-urp@gavo http://code.google.com/p/volute/source/browse/#svn/trunk/projects/theory/snapdm/specification/tap –create table + inserts –VODataService VO-URP SQL query http://www.g-vo.org/SimDB-browser/Query.do http://www.g-vo.org/SimDB-browser/Query.do Not always easy!
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Model complex Normalised (see image) General Abstract –e.g. parameters must be fully defined, no assumptions Hard to deal with quantities with a priori unknown units –ParameterSetting table has value AND unit attributes (Quantity datatype)
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Example queries Find synthetic spectra of white dwarf stars Find cosmological simulations with Ω=0.9, Ω Λ = 0.7 and Ω b =0.02 Find all SPH simulations containing a galaxy cluster with mass around10 14 M sun
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select e.* from experiment e, targetObject t, result r, product p where t.label=white_dwarf and t.containerid=e.id and r.containerid=e.id and r.targetId=t.id and p.containerid=r.id and p.productType=spectrum
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Example queries Find synthetic spectra of white dwarf stars Find (cosmological) simulations with Ω=0.9, Ω Λ = 0.7 and Ω b =0.02 Find all SPH simulations containing a galaxy cluster with mass around10 14 M sun
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select e.* from Experiment e, InputParameter ip1, ParameterSetting ps1, InputParameter ip2, ParameterSetting ps2, InputParameter ip3, ParameterSetting ps3 where ps1.containerId = e.id and ps1.parameterId = ip1.id and ip1.label = omega_lambda and ps1.numericalValue_value=0.7 and ps2.containerId = e.id and ip2.label = omega_baryon and ps2.parameterId = ip1.id and ps2.numericalValue_value=0.02 and ps3.containerId = e.id and ip3.label = omega and ps3.numericalValue_value=0.9
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Example queries Find synthetic spectra of white dwarf stars Find (cosmological) simulations with Ω=0.9, Ω Λ = 0.7 and Ω b =0.02 Find all SPH simulations containing a galaxy cluster with mass around10 14 M sun
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select e.* from Experiment e, ExperimentRepresentationObject ero, RepresentationObjectType rot, TargetObject to, Property p, StatisticalSummary s where ero.containerId = e.id and ero.typeId= rot.id and rot.label=sph.particle and to.containerId = e.id and to.label = galaxy.cluster and p.containerId = to.id and p.label=mass and s.propertyId = p.id and s.statistic = value and s.numericalValue_value=1e14 and s.numericalValue_unit=M_sun
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SELECT r.id as id, r.publisherdid as publisherdid, s0.numericValue_value as mass, s1.numericValue_value as x, s2.numericValue_value as y, s3.numericValue_value as z FROM result r, product o, statisticalsummary s0, property p0, statisticalsummary s1, property p1, statisticalsummary s2, property p2, statisticalsummary s3, property p3 WHERE r.containerid = 6 AND o.containerid = r.id and s0.containerid = o.id and s1.containerid = o.id and s2.containerid = o.id and s3.containerid = o.id and p0.publisherdid = 'mass' and s0.proprtyid=s3.id and s0.statistic = nominal and p1.publisherdid = 'x' and s1.proprtyid=s3.id and s1.statistic = nominal and p2.publisherdid = 'y' and s2.proprtyid=s3.id and s2.statistic = nominal and p3.publisherdid = 'z' and s3.proprtyid=s3.id and s3.statistic = nominal An example from Paris. Find typical values of mass,x,y,z properties in a given simulation result
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SELECT r.id as id, r.publisherdid, max(case when p.publisherdid = mass and s.statistic=nominal then s.numericValue_value else null end) as mass, max(case when p.publisherdid = x and s.statistic=nominal then s.numericValue_value else null end) as x, max(case when p.publisherdid = y and s.statistic=nominal then s.numericValue_value else null end) as y, max(case when p.publisherdid = z and s.statistic=nominal then s.numericValue_value else null end) as z FROM result r, product o, statisticalsummary s, property p WHERE r.containerid = 6 AND o.containerid = r.id and s.containerid = o.id and p.id = s.propertyid group by r.id,r.publisherid,o.id
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Conclusions Some queries can be phrased nicely Others using standard SQL, but due to level of normalisation and abstraction MANY joins required Can we simplify this a bit?
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zoom
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containerIdvalueunitparameterId... 1230.02456 1230.7457 1230.9458 345.04456 345.7457 3451458... idnamelabeldatatypedescription 456omega_bomega.baryonreal... 457omega_lomega.lambdareal... 458omega real... ParameterSetting InputParameter idomega_bomega_lomega... 1230.020.70.9 3450.040.71 + simtap.Experiment
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SimTAP When Protocol is fixed, tap schema can be simplified –parameters columns in simtap.Experiment table –property characterisation columns in product specific characterisation table(s) –...
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select e.* from Experiment e, InputParameter ip1, ParameterSetting ps1, InputParameter ip2, ParameterSetting ps2, InputParameter ip3, ParameterSetting ps3 where ps1.containerId = e.id and ps1.parameterId = ip1.id and ip1.label = omega_lambda and ps1.numericalValue_value=0.7 and ps2.containerId = e.id and ip2.label = omega_baryon and ps2.parameterId = ip1.id and ps2.numericalValue_value=0.02 and ps3.containerId = e.id and ip3.label = omega and ps3.numericalValue_value=0.9 Instead of this
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this select e.* from simtap.Experiment where omegaLambda=0.7 and omegaBaryon=0.02 and omega=0.9
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Table definitions can be derived From a Protocol definition –input parameters –for each Representation object type a table with statistical summaries of properties –target object type ala SimDM (units in ADQL required) pivoted per project? –input data sets (urls) Pivoting queries can be generated
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Proposal SimDAL services MAY include a SimTAP service 1 SimTAP schema per Protocol Each such schema contains –1 Experiment table with columns for parameters –>=1 Product tables with characterisation of properties –Possibly other tables from SimDB/TAP
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