R-GMA – Architecture and Query Mediation 24/4/2003
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Transcript of R-GMA – Architecture and Query Mediation 24/4/2003
WP3
Werner Nutt (Heriot-Watt University)
R-GMA – Architecture and Query Mediation
24/4/2003
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WP3Contributors
• Rob Byrom RAL• Andy Cooke Heriot-Watt• Roney Cordenonsi QMUL• Abdeslem Djaoui RAL• Laurence Field PPARC• Steve Fisher RAL• Alasdair Gray Heriot-Watt• Steve Hicks RAL• Jason Leake RAL• Lisha Ma Heriot-Watt• James Magowan IBM-UK• Werner Nutt Heriot-Watt• Norbert Podhorszki SZTAKI• Manish Soni PPARC• Paul Taylor IBM-UK• Antony Wilson PPARC
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Grid Monitoring: Where are the Concepts?
There are two styles of talking about the Grid:– General metaphors (virtual organisations, services,…)
– Low-level technicalities and jargon (LDAP, XML, SOAP, OGSA, OGSI, ...)
What is missing– Clear definitions of the problems– intuitive concepts for solving them
Needed for communication with both, users and developers
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WP3The Grid Monitoring Problem
In a Grid we have– Computers– Storage elements– Network nodes and connections– Application programmes, …
Monitoring:– What is the current state of the system?– How did the system behave in the past ?
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Monitoring Data Come in two Kinds
A Grid monitoring system makes available two kinds of data
• static data “pools”, e.g., databases on – network topology, nodes connected – applications available (versions, licences, ...)
• “streams” of data, e.g.,– sensor data (cpu load, network traffic, ...)
Data streams may give rise to data pools if they are archived
Today: R-GMA is tailored towards streams, but not pools
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Examples of Monitoring Queries
• “Show me the (average) cpu-load of computers at Heriot-Watt!”
• “Between which nodes was yesterday the average transportation time for 1 MB packets higher than than 0.… seconds?”
• For every node N, how many computers connected to N have currently a cpu-load of no “ more than 30%?”
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Stream Queries can have Various Temporal Interpretations
Consider a query over the relation “Transport Time”
tt(src, dest, pcktSize, method, timestamp, time)
SELECT * FROM ttWHERE src = ral AND dest = bologna
What is meant? Measurements– from now ? (Continuous Query)
– up until now ? (History Query)
– right now ? (Latest Snapshot Query)
Today: Queries can be “flagged” with their type
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Advanced Queries:
Mixing Temporal Query Types
• “Which connections have currently a transportation time that is higher than last week's average?”
(latest snapshot and history)
• “Show me the cpu load of those machines where it is lower than yesterday's load average!”
(continuous and history)
We do not intend to support such queries by R-GMA!
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Architecture Approach 1: A Monitoring Data Warehouse
Idea:– store all data about the Grid status into a huge
database– and query it
Not realistic:• Loading takes time• Data occupy space• Connections to the warehouse may fail• Often monitoring data flow as data streams, and
queries ask for data streams as output
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Approach 2: Monitoring with a “Multi-agent System”
The Grid Monitoring Architecture (GMA) of the Global Grid Forumdistinguishes between:
Consumer
Producer
Monitoring-ApplicationData BaseSensor
DirectoryService
find/register
• Consumers of information
• Producers of information
• Directory Service– Producers register their
supply– Consumers register their
demand
Directory Service mediates between producers and consumers
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WP3Questions about GMA:
• Which kinds of producers and consumers are there?
• In which language do producers register their supply and consumers their demand ?
• What is the meaning of a registration?
• How does a consumer find suitable producers? And how does a producer find suitable consumers?
• Producers have different capabilities to answer queries (e.g. selections, joins, …).
Which of them should they register?
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WP3R-GMA: A Virtual Monitoring
Data Warehouse• Language of producers and consumers:
relational queries (SQL)• Vocabulary: Relations in a global schemaConsumer
DB-Producer
Global Schema S
DB
Stream Producer
Sensor
V1V2...
Vn
VViews on S
Registry
Query • Consumer: poses queries over global schema
• Producer: – has a type (stream p., database p.)
– publishes relations R1, … ,Rk
– for every R, registers a simple view V on the global schema
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WP3Primary Producers
Database producer• supports queries over fixed set of tuples (static queries)
• can be used to publish a database
Stream producer• supports queries over changing set of tuples
(continuous queries)
• supports “latest snapshot queries”– offers up-to-date values for each primary key
Today: DatabaseProducer’s and StreamProducer’s in R-GMA are different from the above!
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Communication Modes of Stream Producers
Stream Producers may offer two communication modes for continuous queries:
– lossless (… but tuples could become stale)– lossy (… but tuples are fresh)
ProducerServlet
IIIIIIII...
Producer ConsumerConsumer
Servlet
IIIIIIII...
Queue Queue
Today: R-GMA’s StreamProducer’s are resilient and support lossless communication
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Republishers Publish Query Answers
Archiver: shows the history of a stream.
Stream Republisher: enables – merging, – thinning, – summarising of streams …
into database into stream
Static Query Materialised View --
ContinuousQuery Archiver
StreamRepublisher
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WP3Republishers in R-GMA Today
Republishers are called “archivers” (although some of them don't archive anything)
An archiver (= republisher)
• is defined by a query • consumes only from “stream producers”• publishes the query result according to its type, using
– a “stream producer”, or– a “latest snapshot producer”, or– a “database producer”
(which keeps an archive)
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Which View should a Republisher Register?
Problem:
Republishers may compute complex queries
… but complex views would confuse the “mediator”!
Ideas:– register a simplified view for a complex query– register a new table
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What is the Meaning of a Query in R-GMA?
Assumption: the views of (primary) producers are selections on a single relation, i.e., queries of the form
SELECT * FROM cpu_load WHERE machine_id = ‘AB123’ AND loc = ‘hw’
(each producer contributes its parts of a relation)
• The virtual database contains the union of the data of all the primary producers
• Conceptually, a query is evaluated over the entire virtual db
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In R-GMA Query Answering Needs MediationSuppose P1, P2 produce for tt (Transport Time)
P1: … WHERE src = hw P2: … WHERE src = ral AND pcktSize > 20
A global consumer poses its query over global relations
SELECT * FROM tt WHERE pcktSize > 10
A mediator translates this into queries over local relations
SELECT * FROM P1.tt WHERE pcktSize > 10UNIONSELECT * FROM P2.tt
Today: R-GMA’s mediator handles simple queries like the one above
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• Global consumers pose queries over global relations
SELECT * FROM tt WHERE pcktSize > 10 ,
which are translated into queries over local relations
SELECT * FROM P1.tt WHERE pcktSize > 10UNIONSELECT * FROM P2.tt
• Local consumers pose queries over local relations directly
SELECT * FROM P1.tt WHERE method = ping
Today: a consumer can be global or local, but local relations cannot be referred to explicitly
Global and Local Consumers
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How does the Mediator Find Suitable Producers?
P1, P2, P3 produce for tt (Transport Time)
P1: … src = hwP2: … src = ral AND pcktSize > 20P3: … src = ral AND method = ping
Q: SELECT * FROM tt WHERE src = ral AND method = ping
We see: P1 is not suitable for Q, but P2 and P3 are. Why?
src = hw AND src = ral AND method = ping is never true
src = ral AND pcktSize > 20 AND … is sometimes true
Satisfiability Test! Today: implemented
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… So Which Producers Should the Mediator Ask?
P2: … src = ral AND pcktSize > 20P3: … src = ral AND method = ping
Q: SELECT * FROM tt WHERE src = ral AND method = ping
All answers to Q returned by P2 are also returned by P3 :
whenever src = ral AND pcktSize > 20 AND src = ral AND method = ping
is true, then src = ral AND method = ping AND src = ral AND method = ping
is true.
Hence, R-GMA only needs to ask P3 Entailment Test!
Today: not implemented
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… But What Did the Producers Promise?
P registers view V
Does P promise– some of V ? (sound description)
– all of V? (sound and complete description)
• The Entailment Test only makes sense when the registered views are sound and complete descriptions
• Producers should register completeness flags
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… Why May a Producer not be Complete?
• The language of views is more restricted than the language of queries
Hence: republishers may be unable to say exactly what they publish
• Archivers may archive in lossy mode
• Producers may lose tuples
• A producer may not know everything about the real world
Open to debate
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WP3Keys in the Global Schema tt(src, dest, method, pcktSize, timestamp, time)
Intuitively, tt has the primary key
(src, dest, method, pcktSize, timestamp).
We need to know the primary keys• to understand the global schema• to answer latest snapshot queries
But can we enforce them?
Sometimes, they hold globally if they hold locally !
Today: global tables have keys, which are used to keep a latest snapshot cache
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WP3Summary (1)
Types of Stream Queries• continuous vs. history vs. latest snapshot
Producers• primary producers vs. republishers
• DB producers: publish database
• stream producers: lossless vs. lossy communication modes
• republishers: materialised views vs. archivers vs. stream republishers
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WP3Summary (2)
Global Schema• primary keys
Consumers• global vs. local consumers
Mediator• translates global query into local queries• applies Satisfiability Test to find suitable producers
Query Planning• Entailment Test• sound vs. sound and complete producers