Scalable Continuous Query System for Internet Databases Jianjun Chen et al Computer Sciences Dept. University of Wisconsin- Madison SIGMOD 2000 Talk by S. Sudarshan
Jan 19, 2018
NiagaraCQ : A Scalable Continuous Query System for Internet Databases Jianjun Chen et al
Computer Sciences Dept. University of Wisconsin-Madison
SIGMOD 2000 Talk by S. Sudarshan
Continuous QueriesExample
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A broad classification Change based Timer based
NiagaraCQA CQ system for the InternetContinuous Queries on XML data setsScalable CQ processingIncremental group optimizationHandles both change based and timer based queries in a uniform way
NiagaraCQ command language
Creating a CQCreate CQ_name XML-QL queryDo action { START start_time} { EVERY
time_interval} { EXPIRE expiration_time}
Delete CQ_name
Expression SignatureQuery examples Where <Quotes><Quote><Symbol>INTC</></></> element_as $g in “http://www.stock.com/quotes.xml”
construct $g
Where <Quotes><Quote><Symbol>MSFT</></></> element_as $g in “http://www.stock.com/quotes.xml”
construct $g
Expression signatures
Quotes.Quote.Symbol in quotes.xml
constant
=
Query plansTrigger Action I Trigger Action J
File Scan
Select Symbol = “MSFT”
Select Symbol = “INTC”
File Scan
quotes.xml quotes.xml
GroupGroup Signature
Common signature of all queries in the group
Group constant table Constant_value
Dest_buffer
INTC Dest. I MSFT Dest. J
The group plan
Incremental Grouping AlgoWhen a new query is submitted
If the expression signature of the new query matches that of existing groups
Break the query plan into two partsRemove the lower partAdd the upper part onto the group
planelse create a new group
Query split with materialized intermediate files
Why not use a pipeline scheme ? Split operator may block simple queries Gives a single complicated execution plan A large portion of query plan may not need to be
executed at each invocation Does not work for grouping timer based queries
Using intermediate files Cut query plan into 2 parts at split operator Add a file scan operator to upper part to read
intermediate file Intermediate files are monitored just like other
data sources
The query split scheme
Trade-offsOther advantages of materialized intermediate files
Only the necessary queries are executed Uniform handling of intermediate files and
original data source files
Disadvantages Split operator becomes a blocking
operator Extra disk I/Os
Range PredicatesE.g. R.a < val or val1 < R.a < val2Multiple such rangesProblem
Intermediate files may contain duplicate tuples
Idea: Virtual intermediate files Use an index to implement this
Incremental grouping of selection predicates
Multiple selection predicates in a query CNF for predicates on same data source Incremental grouping
Choose the most selective conjunct and implement virtual file on this conjunct
Evaluation of other predicates Upper levels of continuous query
Example queryWhere <Quotes><Quote><Symbol>”INTC”</> <Current_Price>$p</></> element_as $g </> in “quotes.xml”, $p < 100Construct $g
Incremental grouping of join operators
A join queryQuotes.Quote.Change_Ratio constant in “quotes.xml”Where <Quotes><Quote><Symbol>$s</></>
element_as $g </> in “quotes.xml”,<Companies><Company><Symbol>$s</></>
element_as $t</> in “companies.xml”construct $g, $t
Queries that contain both join and selection
Example query :Where <Quotes><Quote><Symbol>$s</><Industry>”Computer Service”</></>element_as $g </> in “quotes.xml”,<Companies><Company><Symbol>$s</></>element_as $t</> in “companies.xml”construct $g, $t
Where to place the selection operator ? Below the join
Eliminates irrelevant tuples Above the join
Allows sharing Pick based on cost model
Grouping timer-based queries
Challenge Sharing common computation
Event List Stores time events sorted in time order
Incremental evaluationInvoke queries only on changed data
For each source file, NiagaraCQ keeps a delta file Also for the intermediate files Time stamp store the each tuple
Incremental evaluation of join operators requires complete data files
Memory CachingThousands of continuous queries can’t fit in memoryWhat should we cache ?
Grouped query plans What about non-grouped queries ?
Favor small delta files Front part of the event list
System Architecture
CQ processing
Experimental ResultsExample query :
Where <Quotes><Quote><Symbol>”INTC”</></>element_as $g </> in “quotes.xml”, construct $g
N = number of installed queriesF= number of fired queriesC = number of tuples modified
Performance ResultsCase 1: F=N, C=1000Case 2: F=100, C=1000
Performance ResultsF=N=2000, vary data size
Thank You
OutlineGeneral strategy of incremental group optimizationQuery split with materialized intermediate filesIncremental grouping of selection and join operatorsSystem architectureExperimental results
Incremental group optimization
General Strategy
Why can’t we regroup all queries when a new query is added ?
Use of expression signatures for grouping
Same syntax structure Different constant values