Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
Claims 1-20 are presented for examination.
Claims 1, 2, 3, 5, 7, 9, 11-20 were amended.
This is a Final Action.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
101 rejection for claims 11-16 in view of “computer-readable medium” has been obviated due to current amendment to the claims.
101 abstract idea has been obviated due to current amendment to the claims.
ODP has been maintained and will be obviated when a eTD is provided.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory obviousness-type double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the conflicting application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement.
Effective January 1, 1994, a registered attorney or agent of record may sign a terminal disclaimer. A terminal disclaimer signed by the assignee must fully comply with 37 CFR 3.73(b).
Claims 1-20 are rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1-23 of Patent No. US 11,657,056. Although the conflicting claims are not identical, they are not patentably distinct from each other because
Instant Application
US Patent: US 11,657,056
1, 11, 18
1, 2, 13, 19
2, 12, 19
1, 3, 14-15, 19, 20
3, 13, 20
4. 16-17, 21-22
4, 14
4, 6, 16-17
5, 15
1, 9, 13-17
6, 16
7, 18
7 and 17
9, 17
8
7
9
1, 10-12
10
8, 23
This is an obviousness-type double patenting rejection because the conflicting claims have in fact been patented.
Claims 1-20 are rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1-17 of Patent No. US 12,287,794. Although the conflicting claims are not identical, they are not patentably distinct from each other because
Instant Application
US Patent: US 12,287,794
1, 11, 18
1, 9, 14
2, 12, 19
1, 2, 10, 15
3, 13, 20
3, 11, 15, 16
4, 14
3, 5, 11, 12
5, 15
1, 8, 11, 12
6, 16
6, 13
7, 17
8, 12
8
6
9
1
10
7, 17
This is an obviousness-type double patenting rejection because the conflicting claims have in fact been patented.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-6, 11-16 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Deshmukh et al. (US 2014/0095535) in view of Acker et al. (US 2016/0171067) further in view of Franke et al. (US 8,756,208)
1. Deshmukh teaches, A method for processing a continuous data stream of events using a distributed event processing system (Abstract – techniques for managing continuous queries with archived relations… a query that includes at least a data stream… evaluated based at least in part on the data stream…, Deshmukh ), the method comprising:
receiving, by a computer device, an event from a continuous data stream of events (Paragraph 3 - teaches modern applications and systems… generate data in the form of continuous data or event streams, the query may comprise a continuous query configured to process incoming real-time data of the data stream – thus teaching receiving/processing incoming real-time events from a continuous stream, Deshmukh);
executing, by the computing device, a plurality of continuous queries against the set of de-serialized data values corresponding to the attribute to generate a plurality of output event streams (Paragraph 5 – teaches the query may comprise a continuous query configured to process incoming real-time data… evaluating the query… based on the data stream, Fig 1: 156 – SQ Engine producing outputs – teaches executing continuous queries over event streams, Deshmukh ); and
transmitting, by the computing device, the plurality of output event streams to a user device (Fig 3, Paragraphs 159 – 162 – teaches processing the selecting events then outputting to event sinks including a cache Deshmukh).
Deshmukh does not explicitly recite,
determining, by the computing device, that a data type of an attribute associated with the event is of a numeric data type;
responsive to determining that the data type of the attribute is of the numeric data type, computing, by the computing device, a number of bits for storing a plurality of values of the attribute;
determining, by the computing device, that a first type of data compression is to be performed on the plurality of values of the attribute based at least in part on the computed number of bits and a set of unique values represented by the attribute;
generating, by the computing device, a set of serialized data values for the attribute of the event based at least in part on the first type of data compression;
generating, by the computing device, a set of de-serialized data values for the attribute of the event based at least in part on the first type of data compression and the set of serialized data values;
However, Acker teaches,
determining, by the computing device, that a data type of an attribute associated with the event is of a numeric data type (Paragraph 8 - determining a variable serialization scheme associated with the data based on the variable type and if the variable type is integer, determining that the variable serialization comprises an integer scheme, Acker);
generating, by the computing device, a set of serialized data values for the attribute of the event based at least in part on the first type of data compression (Paragraph 26-28 – teaches a fast serialization schemes can use the knowledge about data format, data content… minimal value, maximal value, value set or dictionary… fast serialization schemes may be used… to reduce the amount of data during the serialization/deserialization – thus teaching general serialized value and explicitly reducing size via compression (serialization schemes), Acker );
generating, by the computing device, a set of de-serialized data values for the attribute of the event based at least in part on the first type of data compression and the set of serialized data values (Paragraph 48 and Fig 1 – teaches deserialization engine 148 and abstract – teaches transferring the serialized data to the second database… the target system can read the transferred data from the transfer medium and deserialize the transferred data, Acker);
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains to combine Deshmukh with Acker because Acker paragraph 27-29 teaches selective combinations of data compression and serialization to optimize data transfer rates, and Acker at paragraph 48 teaches data streaming compatible with Deshmukh’s continuous queries. A POSITA would incorporate Acker’s serialization/compression into Deshmukh’s event-stream system because Deshmukh handles high-volume streams, and Acker provides known methods for reducing message size to improve throughput.
Franke teaches,
responsive to determining that the data type of the attribute is of the numeric data type, computing, by the computing device, a number of bits for storing a plurality of values of the attribute (Col 3: lines 51-56 - teaches data attributes are encoded based on distinct values. A number of bits are used to represent these values for storage savings. Typically, there is one encoded value for each distinct attribute value. For example, a data attribute corresponding to months of the year may be represented by only four bits, Franke);
determining, by the computing device, that a first type of data compression is to be performed on the plurality of values of the attribute based at least in part on the computed number of bits and a set of unique values represented by the attribute (Col 2: lines 63-67, Col 3: lines 51-52 & Col 3: 66-67 – Col 4: lines 1-2 – teaches data attributes are encoded based on distinct valuesl A number of bits are used to represent these values for storage savings; as the amount of data grows and the number of distinct data values increases… a new encoding scheme with more encoding bits is required, Franke);
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains to modify the Deshmukh/Acker system to include Franke’s encoded data processing techniques because the combination merely applies a known data-encoding optimization to known distributed continuous query/event stream processing system. A POSITA would have been motivated to incorporate Franke’s distinct-value/bit-width encoding into Acker’s serialization layer before Deshmukh’s continuous query processing, because Franke expressly identifies the same design goal: reducing storage requirements and bandwidth needed to transfer data between computer nodes. The substitution would have yielded predictable results of smaller encoded event attributes, reduced network/storage overhead, and more efficient downstream continuous query processing without changing Deshmukh’s query execution model.
2. The combination of Deshmukh, Acker and Franke teach, The method of claim 1, further comprising:
receiving a batch of events from the continuous data stream of events (Paragraph 3 – teaches a number of modern applications generate data in the form of continuous data or event streams; Fig. 6: 604 – teaches initialize the query with historical data, step 606 – teaches evaluate the query based on the data stream and historical data – these steps show processing sets of events together (historical with incoming), Deshmukh); and
identifying the first type of data compression performed on the plurality of data values represented by the attribute of the event in the batch of events (Paragraph 26-28 – teaches fast serialization schemes can use the knowledge about data format, data content… minimal value, maximal value, value set or dictionary… During the analyzing process, it may be determined whether to use compression scheme, fast serialization schemes, or a combination therefore – further knowledge can be obtained during an analyzing process before serialization – thus teaching analyzing process that identifies which compression/serialization scheme applies based on attribute values, Acker).
3. The combination of Deshmukh, Acker and Franke teach, The method of claim 1, further comprising identifying a second type of data compression performed on the plurality of data values represented by the attribute of the event (Paragraph 28 – teaches fast serialization schemes can use knowledge about data format, data content… During the analyzing process, it may be determined whether to use compression scheme, fast serialization schemes or a combination thereof; Paragraphs 7-8 & 30-34 – teaches dynamic determination of different serialization schemes (repetition, replication, integer, character) – thus teaching multiple distinct compression/serialization schemes and identifying which one applies during analysis, Acker), wherein the second type of data compression is different from the first type of data compression (Paragraphs 7-8 & 33-35 – teaches determining the data serialization scheme… comprises at least one of repetition scheme or a replication scheme… determining the variable serialization scheme.. comprises an integer scheme or a character scheme – thus showing multiple different, alternative schemes, Acker).
4. The combination of Deshmukh, Acker and Franke teach, The method of claim 3, further comprising:
generating the set of serialized data values for the attribute based at least in part on the second type of data compression (Paragraphs 7-10 & 33-35 – teaches determining the data serialization scheme comprises at least one of a repetition scheme or a replication scheme; determining the variable serialization scheme comprises an integer scheme or a character scheme – the system selects different schemes for compression and serialization, Acker); and
generating the set of de-serialized data values for the attribute based at least in part on the second type of data compression and the set of serialized data values (Fig 1: 148 – teaches Deserialization engine and Abstract, Paragraph 1 – teaches the target system can deserialize the transfer data – thus teaching corresponding deserialization processes for repetition vs replication schemes (i.e. different decompression paths), the second type is simply the alternative serialization scheme, Acker).
5. The combination of Deshmukh, Acker and Franke teach, The method of claim 1 wherein:
the first type of data compression is performed on the plurality of data values represented by the attribute based at least in part on determining that the attribute is of the numeric data type (Paragraph 8 – teaches if the variable type is integer, determining that variable serialization comprises an integer scheme; and if the variable type is character, determining that the variable serialization comprises a character scheme; Paragraph 26-28 – teach selecting schemes based on data characteristics, Acker).
6. The combination of Deshmukh, Acker and Franke teach, The method of claim 5, wherein the first type of data compression is at least one of a base value compression (Paragraph 28-29 – teaches the knowledge of data content may include minimal value, maximal value, value set… In some cases, this knowledge can be obtained during an analyzing process… determining minimal value, maximal value for base-value encoding, Acher), a precision reduction compression, or a precision reduction value index compression.
Claims 11 and 18 are similar to claim 1 hence rejected similarly.
Claims 12 and 19 are similar to claim 2 hence rejected similarly.
Claims 13 and 20 are similar to claim 3 hence rejected similarly.
Claim 13 further includes “…in the batch of events”
Claim 14 is similar to claim 4 hence rejected similarly.
Claim 15 is similar to claim 5 hence rejected similarly.
Claim 16 is similar to claim 6 hence rejected similarly.
Claims 7, 8 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Deshmukh et al. (US 2014/0095535) in view of Acker et al. (US 2016/0171067) and Franke et al. (US 8,756,208) further in view of Al-Dossary et al. (US 2015/0094958)
All the limitations of claim 1 are taught above.
7. The combination of Deshmukh, Acker and Franke teach, The method of claim 1 further comprising:
determining that the attribute is of a second data type and wherein: wherein the second data type is a non-numeric data type (Paragraph 28 – teaches the Knowledge about data format may include character, integer or other formats, Paragraph 34 – teaches distinguishes characters from integer serialization schema – thus teaching identifying non-numeric types such as character fields during serialization analysis, Acker).
The combination of Deshmukh and Acker do not explicitly teach,
a second type of data compression is performed on a plurality of data values represented by the attribute based at least in part on determining that the attribute is of the second data type (non-numeric).
However, Al-Dossary teaches,
a second type of data compression is performed on a plurality of data values represented by the attribute based at least in part on determining that the attribute is of the second data type (non-numeric) (Abstract, Paragraphs 7-8 – teaches extended quantization… group reduction criteria… handling attributes that have non-numeric or categorical values through grouping and merging techniques – thus teaching quantization/grouping of categorical attribute values, Al-Dossary).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains to modify the combination of Deshmukh and Acker with Al-Dossary because Deshmukh’s event stream systems must optimize both numeric and non-numeric attribute transport, Acker identifies the type and Al-Dossary supplies the appropriate compression for non-numeric data. Both techniques target bandwidth and memory reduction. A POSITA would combine Al-Dossary’s grouping/quantization compression with Deshmukh’s event processing to reduce payload size for text/categorical fields further enhancing Acker’s numeric compression and enhances performance in distributed CQ system.
8. The combination of Deshmukh, Acker, Franke and Al-Dossary teach, The method of claim 7, wherein the second type of data compression is a value index compression technique (Abstract, Paragraph 7 – 8 – extended quantization… merging attributes… reducing attribute values into representative groups… - thus teaching grouping categorical values into quantization groups which represented internally by group identifiers (indexes), Al-Dossary).
Claim 17 is similar to claim 7 hence rejected similarly.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over Deshmukh et al. (US 2014/0095535) in view of Acker et al. (US 2016/0171067) and Franke et al. (US 8,756,208) further in view of Draese et al. (US 8,442,988)
All the limitations of claim 1 is taught above.
9. The combination of Deshmukh, Acker and Franke teach, The method of claim 1, wherein generating the set of serialized data values for the attribute based on the first type of data compression comprises:
obtaining a minimum data value, a maximum data value of the attribute (Paragraph 28 – teaches the knowledge about data content may include minimal value, maximal value, value set or dictionary – thus teaching obtaining min/max value and value set (unique values), Acker); and
…to generate the set of serialized data values for the attribute (Claim 1 - serializing the data stored in the first database using the data serialization scheme associated with the data and the variable serialization scheme associated with the data, Acker)
The combination of Deshmukh, Acker and Franke do not explicitly teach,
determining that a size of the set of unique data values is smaller than the plurality of data values represented by the attribute is smaller than the plurality of data values of the attribute; and
responsive to the determining, performing the first type of data compression on the plurality data values represented by the attribute for the event based at least in part on the computed number of bits for storing the plurality of values of the attribute and the set of unique values represented by the attribute to generate the set of serialized data values for the attribute.
However, Draese teaches,
determining that a size of the set of unique data values is smaller than the plurality of data values represented by the attribute is smaller than the plurality of data values of the attribute (Col 9: lines 3-8 - teaches we start with compressed data in cells, and go through the cels to collect distinct values that actually appear separately for each of them. If the set of distinct values is much smaller than the values in the global dictionary, we create a cell-specific dictionary that only contains those values that actually appear, Draese); and
responsive to the determining, performing the first type of data compression on the plurality data values represented by the attribute for the event (Col 9: lines 3-8 - teaches If the set of distinct values is much smaller than the values in the global dictionary, we create a cell-specific dictionary that only contains those values that actually appear, Draese) based at least in part on the computed number of bits for storing the plurality of values of the attribute and the set of unique values represented by the attribute (Col 9: lines 9-10 – teaches the actual criteria for ‘much fewer’ are based on the number of bits that can be saved , Draese – in combination with, Col 3: lines 51-54 of Franke – discloses Draese tying decision to bit savings while Franke teaches encoding distinct values using a number of bits. Together, they support compression based on computed bits and unique/distinct value).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains to add Draese’s cell specific decision logic to the Deshmukh/Acker/Franke system because Deshmukh processes high-volume continuous event streams, Acker already analyzes attributes for serialization using min/max/value set information, and Franke teaches bit-width encoding of distinct values for storage savings. Draese supplies the predictable optimization of applying a smaller dictionary when the actual distinct-value set is much smaller and when bit savings justify it. This would reduce serialized event-attribute size before continuous query execution with predictable improvement in storage, bandwidth and processing efficiency.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Deshmukh et al. (US 2014/0095535) in view of Acker et al. (US 2016/0171067) and Franke et al. (US 8,756,208) further in view of Jerzak et al. (US 2015/0169786)
All the limitations of claim 1 are taught above.
10. The combination of Deshmukh, Acker and Franke do not explicitly teach,
identifying a set of one or more operations to be performed on the event in a batch of events based on the plurality of continuous queries;
representing the set of one or more operations as a continuous query language (CQL) Resilient Distributed Dataset (RDD) Directed Acyclic Graph (DAG) of transformations; and
executing the CQL RDD transformations against the set of de-serialized data values corresponding to the attribute to generate the plurality of output event streams.
However, Jerzak teaches,
identifying a set of one or more operations to be performed on the event in a batch of events based on the plurality of continuous queries (Paragraph 3 – Within an ESP system a continuous data stream (comprising multiple, consecutive data items) is pushed through a query. Results of the query are subsequently pushed out of the system. Queries in ESP system can be decomposed into a network of operators, each operator representing an atomic processing block. The operator network forms a DAG, Jerzak);
representing the set of one or more operations as a continuous query language (CQL) Resilient Distributed Dataset (RDD) Directed Acyclic Graph (DAG) of transformations (Paragraph 3 – teaches an event-stream continuous query (CQL), and Paragraph 17 With Fig 2 – teaches a parsed ESP query (e.g. parsed query 109) can be represented as a DAG, Jerzak); and
executing the CQL RDD transformations against the set of de-serialized data values corresponding to the attribute to generate the plurality of output event streams (Paragraphs 3, 21, 42-43, Fig 3 and Fig 6 – teaches at operation 612 a merge node is created in the DAG 300, the merge node consolidating data from the grouping and the duplicates of the grouping. At operation 614 the input query is resolved by processing data from one or more event streams 104A-104E using the DAG 300).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which said subject matter pertains to modify the combination of Deshmukh/Acker/Franke with Jerzak because both references are complementary event stream processors, and their similarities and overlap are such that appearances of features shown in one would suggest the application of those features to the other to a POSITA and the elements can be combined according to known methods to yield predictable results, without any change in the element’s respective functions. One would have been motivated to modify Deshmukh with Jerzak to improve processing efficiency because Jerzak discloses methods “to create an optimal partitioned query 112 (an optimal DAG) to better utilize system resources” (Paragraph 15, Jerzak).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/AMRESH SINGH/Primary Examiner, Art Unit 2159
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