Ex Parte C N et al

Patent Trial and Appeal Board

Nov 25, 2013

11770926 (P.T.A.B. Nov. 25, 2013)

UNITED STATES PATENT AND TRADEMARK OFFICE
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
Address: COMMISSIONER FOR PATENTS
P.O. Box 1450
Alexandria, Virginia 22313-1450
www.uspto.gov
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO.
11/770,926 06/29/2007 Kanthi C N C N 1-4-72-1 7141
46304 7590 11/26/2013
RYAN, MASON & LEWIS, LLP
48 South Service Road
Suite 100
Melville, NY 11747
EXAMINER
ALAM, SHAHID AL
ART UNIT PAPER NUMBER
2162
MAIL DATE DELIVERY MODE
11/26/2013 PAPER
Please find below and/or attached an Office communication concerning this application or proceeding.
The time period for reply, if any, is set in the attached communication.
PTOL-90A (Rev. 04/07)

UNITED STATES PATENT AND TRADEMARK OFFICE
____________________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
____________________

Ex parte KANTHI C N, NAIDU K V M, RAJEEV RASTOGI,
and SCOTT SATKIN
____________________

Appeal 2011-006655
Application 11/770,926
Technology Center 2100
____________________

Before ST. JOHN COURTENAY, III, THU A. DANG,
and CARL W. WHITEHEAD, JR., Administrative Patent Judges.

DANG, Administrative Patent Judge.

DECISION ON APPEAL

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Application 11/770,926

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I. STATEMENT OF THE CASE
Appellants appeal under 35 U.S.C. § 134(a) from a Final Rejection of
claims 1-6 and 8-19 (App. Br. 2). Claims 7 and 20 are allowed (id.). We
have jurisdiction under 35 U.S.C. § 6(b).
We affirm.

A. INVENTION
Appellants’ invention is directed to generating a query plan for
executing a set of aggregate queries to be executed on a data stream which
generates at least one intermediate aggregate query that combines a subset of
aggregate queries to pre-aggregate data from the data stream prior to
execution of the subset of aggregate queries, to reduce the number of
computations required (Abstract).

B. ILLUSTRATIVE CLAIM
Claim 1 is exemplary:
1. A method, comprising:
obtaining a data stream;
obtaining a set of aggregate queries to be executed on the
data stream; and
generating a query plan for executing the set of aggregate
queries on the data stream, wherein the generated query plan
comprises generating at least one intermediate aggregate query,
wherein the intermediate aggregate query combines a subset of
aggregate queries from the set of aggregate queries so as to pre-
aggregate data from the data stream prior to execution of the
subset of aggregate queries such that the generated query plan is
optimized for computational expense based on a given cost
model;
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wherein the generation of the query plan is implemented
by executing one or more software programs on a processor
device.

C. REJECTIONS
The prior art relied upon by the Examiner in rejecting the claims on
appeal is:
Levy US 5,659,725 Aug. 19, 1997
Agrawal US 5,832,475 Nov. 3, 1998
Lohman US 6,092,062 Jul. 18, 2000

Claims 1, 2, 4-6, 10-15, and 17-19 stand rejected under 35 U.S.C.
§ 102(b) as being anticipated by Levy.
Claims 3, 8, and 16 stand rejected under 35 U.S.C. § 103(a) as being
unpatentable over Levy in view of Agrawal.
Claim 9 stands rejected under 35 U.S.C. § 103(a) as being
unpatentable over Levy in view of Lohman.

II. ISSUE
The dispositive issues before us are whether the Examiner has erred in
determining that Levy teaches “generating a query plan for executing a set
of aggregate queries on the data stream” that comprises “generating at least
one intermediate aggregate query” (claim 1, emphasis added).

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III. FINDINGS OF FACT
The following Findings of Fact (FF) are shown by a preponderance of
the evidence.
The Invention
1. According to Appellants, an “aggregate tree is a directed tree
with: (1) a special root node corresponding to the input stream; and (2) other
nodes corresponding to aggregates” (Supp. Spec. 17:1-2).
Levy
2. Levy discloses that query optimization which is done by
making a graph of the query and moving predicates (such as type = “Govt”)
around in the graph so that they will be applied early in the optimized query
generated from the graph (Abstract; col. 5, ll. 36-40). Techniques for
applying predicates as early (early execution) as possible are applied to a
query graph, which is a data structure that represents the query during
optimization; wherein, each of the query’s sub-queries and views forms a
block of the query graph (col. 2, ll. 14-20).
3. In particular, aggregate query, foreign accounts fgAccounts
103 lists all foreign accounts of type “Govt” that are not secret accounts
(Fig. 1; col. 4, ll. 49-56). A second aggregate query for potential customers
ptCustomers 107 selects calls longer than 2 minutes and then finds, for each
customer with a silver level membership, the maximum length amongst all
his calls to each area code other than the customer’s own area code (Fig. 1;
col. 4, ll. 57-61). Query Q1 107, defined in terms of fgAccounts 103 and
ptCustomers 107, looks for potential customers among foreign
governments that make calls longer than 50 minutes to area codes in which
some promotion is planned (Fig. 1; col. 4, ll. 62-66).
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4. In query Q1 107, the views fgAccounts 103 and ptCustomers
105 are joined on a key of the customers relation and, therefore, the
predicate, Type=“Govt,” can be moved from fgAccounts into the definition
of ptCustomers (Fig. 2; col. 5, ll. 36-40)
Lohman
5. Lohman discloses an SQL optimizer that is conventionally
provided with system information such as the location of tables and parts of
tables, the size of such tables, network node locations, system operating
characteristics and statistics (col. 7, l. 65-col. 8, l. 2).

IV. ANALYSIS
Claims 1, 2, 4, 10, 14, 15, and 17
As for claim 1, Appellants contend that, in Levy, “query Q1 is
executed after [the aggregate query] views ptCustomers and fgAccounts”
and that “query Q1 is executed on the results generated by views
ptCustomers and fgAccounts” (App. Br. 6, emphasis added). Thus,
Appellants contend that Levy does not disclose an “intermediate aggregate
query” that pre-aggregates data from the data stream “prior to execution of
the subset of aggregate queries” as required by claim 1 (id.).
However, we give the claim its broadest reasonable interpretation
consistent with the Specification. See In re Morris, 127 F.3d 1048, 1054
(Fed. Cir. 1997). We note that claim 1 merely recites a method comprising
“generating a query plan for executing a set of aggregate queries” wherein
the “plan” comprises “generating at least one intermediate aggregate query”
(emphasis added). That is, claim 1 does not positively recite any step of
“executing” aggregate queries or “generating” intermediate aggregate
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queries, but rather, generating a “plan” for the intended purpose “for
executing” aggregate queries, wherein the generated plan includes
“generating” intermediate aggregate queries.
We find “executing the set of aggregate queries” and “generating at
least one intermediate aggregate query” are merely intended purpose and use
of the “plan” generated by the claimed step, which do not limit the claim.
Particularly, an intended purpose or use will not limit the scope of the claim
because it merely defines a context in which the invention operates.
Boehringer Ingelheim Vetmedica, Inc. v. Schering-Plough Corp., 320 F.3d
1339, 1345 (Fed. Cir. 2003). That is, the intended purpose of “for
executing” of the plan that comprises the intended use of “generating” an
intermediate aggregate query will not limit the scope of claim 1.
Thus, we give claim 1 its broadest reasonable interpretation as merely
requiring generating a query plan.
Furthermore, we also note that “a query plan” is merely the type of
data being generated in the claimed method, but the informational content of
the data does not change the functionality of or provide an additional
function to the “generating” step, i.e., does not limit how the data is
generated. Non-functional descriptive material will not distinguish the
invention from the prior art in terms of patentability. See In re Ngai, 367
F.3d 1336, 1339 (Fed. Cir. 2004) and In re Gulack, 703 F.2d 1381, 1385
(Fed. Circ. 1983). Thus, we give generating “a query plan” its broadest
reasonable interpretation as generating any type of data relating to a query.
Levy discloses that query optimization which is done by making a
graph of the query and moving predicates (such as type = “Govt”) around in
the graph so that they will be applied early in the optimized query generated
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from the graph (FF 2). The query graph is a data structure that represents
the query during optimization; wherein, each of the query’s sub-queries and
views forms a block of the query graph (id.). In particular, query Q1,
defined in terms of aggregate queries, fgAccounts and ptCustomers, forms
part of the query graph (FF 3).
We find that query graph including query Q1 that combines the results
from aggregate queries fgAccounts and ptCustomers comprises data that
may be generated relating to a query. In view of our claim construction
above, we find no error in the Examiner’s finding that Levy discloses the
contested claim limitations of claim 1.
Accordingly, we find no error in the Examiner’s anticipation rejection
of claim 1 under over Levy. Further, independent claims 14 having similar
claim language and claims 2, 4, 10, 15, and 17 (depending from claims 1 and
14) which have not been argued separately, fall with claim 1.
Claims 5, 6, 18, and 19
As for claim 5, Appellants contend that Levy’s query tree “is not an
aggregate tree as defined by Appellants in the present [S]pecification,” “‘a
directed tree with: (1) a special root node corresponding to the input stream;
and (2) other nodes corresponding to aggregates’” (App. Br. 7). However,
the Examiner finds that Levy discloses “cost-based optimization [which]
minimizes the computation cost, and the optimized tree for a query plan
[where] the aggregate operations is a minimum-cost aggregate tree” (Ans.
6).
Claim 5 does not define “aggregate tree,” and the Specification
merely defines an aggregate tree as a directed tree having a root node
corresponding to the input stream and other nodes corresponding to
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aggregates (FF 1). Thus, we give “aggregate tree” its broadest reasonable
interpretation as a tree having a root node (relative to input) and other nodes
(relative to aggregates).
As noted supra, Levy discloses a query graph including query view
Q1 and aggregate queries views, fgAccounts and ptCustomers (FF 3). We
adopt the Examiner’s finding that query view Q1 represents a root node and
that the aggregate query views represent the other nodes relative to
aggregates. That is, Levy’s query optimization graph comprises an
“aggregate tree” (claim 5).
Accordingly, we find no error in the Examiner’s anticipation rejection
of claim claim 5 under 35 U.S.C. § 102(b) over Levy. Claims 6, 18, and 19
which have not been argued separately, fall with claim 5.
Claims 11-13
As for claim 11, Appellants contend that “Levy teaches an
arrangement in which a single predicate in a single original view is
duplicated such that similar predicates are present in multiple optimized
views” (App. Br. 8), and thus, Levy does not disclose “generating a query
plan” wherein the plan “comprises identifying similar filters” and
“combining the similar filters” of claim 11 (id.).
However, similar to the claim 1, claim 11 merely recites a method
comprising “generating a query plan for executing a set of aggregate
queries” wherein the “plan” comprises “identifying” similar filters and
“combining” the similar filters. That is, claim 11 does not positively recite
any step of “identifying” or “combining” filters, but rather, the claimed
method merely generates a “plan” with the intended use of “identifying” and
“combining” filters.
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Furthermore, like claim 1, claim 11’s “query plan” is merely the type
of data being generated, but the informational content of the data does not
limit how the data is generated.
Thus, given its broadest reasonable interpretation, like claim 1, claim
11 merely requires the step of generating a query plan, i.e., generating data
relating to a query. As noted supra, we find that Levy discloses generating
data relating to a query.
Accordingly, we also find no error in the Examiner’s anticipation
rejection of claim 11 under 35 U.S.C. § 102(b) over Levy. Further, claims
12 and 13 (depending from claims 11) which have not been argued
separately, fall with claim 11.
Claim 9
Appellants contend that “[n]owhere does Lohman teach or suggest
that data records themselves comprise attributes that describe flow statistics
in the data network” (App. Br. 10), and thus, Lohman does not disclose “the
data stream comprises records . . . wherein each of the data records
comprises attributes” of claim 9.
However, “data stream” is merely the type of data obtained in the
claimed method of claim 1 from which claim 9 depends, wherein “records”
are merely data comprised within the obtained data, and “attributes” are
merely data comprised within such data. Thus, claim 9 merely requires that
the obtained data comprising various data therein.
Lohman discloses an SQL optimizer that is provided with information
relating to statistics (FF 5). We find that the combination of Levy and
Lohman at least suggests the contested claim limitations of claim 9.
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Thus, we find no error in the Examiner’s rejection of claim 9 under
35 U.S.C. § 103(a) over Levy in view of Lohman.
Claims 3, 8, and 16
Appellants argue that claims 3, 8, and 16 are patentable over the cited
prior art for the same reasons asserted with respect to claim 1 (App. Br. 9-
10). However, as noted supra, we find that Levy teaches all the features of
claim 1. We therefore also affirm the Examiner’s § 103 rejection of claims
3, 8, and 16 under 35 U.S.C. § 103 over Levy in view of Agrawal.

V. CONCLUSION AND DECISION
The Examiner’s rejection of claims 1, 2, 4-6, 10-15, and 17-19 under
35 U.S.C. § 102(b) and claims 3, 8, 9, and 16 under 35 U.S.C. § 103(a) is
affirmed.
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a)(1)(iv).

AFFIRMED

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