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
The pending claims 1-20 are presented for examination.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 8/20/2025 has been considered by the examiner. Please see attached PTO-1449.
Claim Objections
Claims 2, 3, 5, 8, 12, 13, 15 and 18 are objected to because of the following informalities:
As to claim 2, line 4, recites “enables” performing functionality. It indicates intended use; Minton v. Nat ’l Ass ’n of Securities Dealers, Inc., 336 F.3d 1373, 1381, 67 USPQ2d 1614, 1620 (Fed. Cir. 2003) “whereby clause in a method claim is not given weight when it simply expresses the intended result of a process step positively recited.” Examples of claim language, although not exhaustive, that may raise a question as to the limiting effect of the language in a claim are: (A) “adapted to” or “adapted for” clauses; (B) “wherein” clauses; and (C) “whereby” clauses. Therefore intended use limitations are not required to be taught, see MPEP 2111.04.
Similar problem exists in claims 3, 8, 12, 13 and 18.
Claim 5, line 5, recites “when” is an optional statement. Claim scope is not limited by claim language that suggests or makes optional but does not require steps to be performed, or by claim language that does not limit a claim to a particular structure, see MPEP 2111.04.
Similar problem exists in claim 15.
As to claim 8, line 5, recites “allows” performing functionality. It indicates intended use; Minton v. Nat ’l Ass ’n of Securities Dealers, Inc., 336 F.3d 1373, 1381, 67 USPQ2d 1614, 1620 (Fed. Cir. 2003) “whereby clause in a method claim is not given weight when it simply expresses the intended result of a process step positively recited.” Examples of claim language, although not exhaustive, that may raise a question as to the limiting effect of the language in a claim are: (A) “adapted to” or “adapted for” clauses; (B) “wherein” clauses; and (C) “whereby” clauses. Therefore intended use limitations are not required to be taught, see MPEP 2111.04.
Similar problem exists in claim 18.
Appropriate correction is required.
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 reference 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. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/forms/. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to http://www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claim 1 is provisionally rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claim 1 of Patent 12,321,361.
Although the conflicting claims are not identical, they are not patentably distinct from each other because the inventions are obvious variants. Claim 1 of the Instant application substantially recites the limitations of claim 1 of Patent 12,321,361 as shown in comparison table below.
Instant Application
Patent 12,321,361
1. A system comprising:
at least one hardware processor; and
a memory storing instructions that cause the at least one hardware processor to perform operations comprising:
receiving a first semi-structured object;
iterating through a list of fields specified by a target object type;
for each field, determining whether a field with a same name is present in the first semi-structured object;
in response to the field being found in the first semi-structured object, converting a value of the field to a target field type according to defined type conversion rules;
storing the converted value in a unified representation comprising a data structure that stores both structured and semi-structured data types; and
processing a query using the unified representation.
2. The system of claim 1, wherein the unified representation being provided in storage and in memory during query processing, the unified representation comprising a set of structured type fields that include a set of semi-structured typed fields that enables type validation and schema enforcement for the set of structured type fields.
1. A system comprising:
at least one hardware processor; and
a memory storing instructions that cause the at least one hardware processor to perform operations comprising:
receiving a query, the query referencing a unified representation for structured type data and semi-structured type data, the unified representation being provided in storage and in memory during query processing, the unified representation comprising a set of structured type fields that include a set of semi-structured typed fields that enables type safety and enforcement for the set of structured type fields, and flexibility for the set of semi-structured typed fields in a same column, the unified representation in storage including type information for the semi-structured type data as part of the semi-structured type data, the unified representation being utilized for structured type data and semi-structured type data; processing the query using the unified representation stored in the memory, the unified representation providing performance parity between structured type data and semi-structured type data;
receiving a set of code statements, the set of code statements including first code indicating a particular structured data type;
determining that the set of code statements includes a definition of content type for an array, an object, or a map;
determining that the set of code statements includes second code to perform a type conversion from the particular structured data type to a particular semi-structured data type; and
performing, using the second code, the type conversion from the particular structured data type to the particular semi-structured data type based at least in part on the definition of content type.
Although the conflicting claims are not identical, they are not patentably distinct from each other because they are substantially similar in scope and they use the same limitations.
It would have been obvious to a person of ordinary skill in the art at the time the invention was made to combine claim 1 and claim 2 of the Instant application of to arrive at the claims 1 of Patent 12,321,361 because the person would have realized that the remaining element would perform the same functions as before. “Omission of element and its function in combination is obvious expedient if the remaining elements perform same functions as before.” See In re Karlson (CCPA) 136 USPQ 184, decide Jan 16, 1963, Appl. No. 6857, U. S. Court of Customs and Patent Appeals.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 11 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (U.S. Pat. Pub. 2024/0086464) in view of Christianson et al. (U.S. Pat. Pub. 2002/0120630).
Referring to claim 1, Tian et al. teaches a system comprising:
at least one hardware processor (processors, see Tian et al., Para. 6); and
a memory (memory, see Tian et al., Para. 6) storing instructions that cause the at least one hardware processor to perform operations comprising:
receiving a first semi-structured object (At 705, the first JSON record may be fetched/obtained from the JSON array, see Tian et al., Para. 114, semi-structured data, such as JSON data, , see Tian et al., Para. 55);
iterating through a list of fields specified by a target object type (At 715, it can be determined whether the first attribute name 'counties' is in the first JSON record, see Tian et al., Para. 115,…, for the first internal object ({'name': 'Dade', 'population': 12345}), the value for 'counties.name' may be determined as 'Dade', and the value for 'counties.population' may be determined as '12345', see Tian et al., Para. 115);
for each field, determining whether a field with a same name is present in the first semi-structured object (As the first attribute name 'counties' is not found, see Tian et al., Para. 125);
in response to the field being found in the first semi-structured object, converting a value of the field to a target field type (for the attributes with the attribute values in the simple data types, such as string, number, Boolean, null, metadata collection module 410 may determine a plurality of attribute names, see Tian et al., Para. 67. At 715, it can be determined whether the first attribute name 'counties' is in the first JSON record,…, for the first internal object ({'name': 'Dade', 'population': 12345}), the value for 'counties.name' may be determined as 'Dade', and the value for 'counties.population' may be determined as '12345', see Tian et al., Para. 115);
storing the converted value in a unified representation (a plurality sets of values and/or appended set of values may be output in queue. In some embodiments, the output queue may be stored in a table in a relational database, see Tian et al., Para. 90) comprising a data structure that stores both structured and semi-structured data types (The output values may be stored in a table with reference to the structured format, see Tian et al., Para. 127, the structured format may be stored in a table with a single row, for example. Each column of the table may store one of the components, see Tian et al., Para. 70).
However, Tian et al. does not explicitly teach
according to defined type conversion rules;
(for each of the plurality of attribute names in the metadata, the format generation module 420 may determine a first presence ratio of the attribute name present in the predetermined number of records… If the first presence ratio is higher than a predetermined ratio threshold for the attribute name, the format generation module 420 may determine the attribute name as a first component of the structured format, see Tian et al., Para. 72)
processing a query using the unified representation.
Christianson et al. teaches
according to defined type conversion rules (A significant limitation of these and other current conversion approaches is that mapping between structured and semi-structured data formats is by way of applying a fixed set of "rules" to perform the mapping…a given semi-structured input, the conversion rules control conversion into corresponding structured database output, see Christianson et al., Para. 11);
processing a query using the unified representation (an SQL query, that is appropriate for accessing the legacy database, see Christianson et al., Para. 63, and, a plurality sets of values and/or appended set of values may be output in queue. In some embodiments, the output queue may be stored in a table in a relational database, see Tian et al., Para. 90).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Tian et al., to have according to defined type conversion rules; processing a query using the unified representation, as taught by Christianson et al., to have a more flexible approach to handling semi-structured data in a structured manner (Christianson et al., Para. 12).
Referring to claim 11, Tian et al. teaches a method, which recites the corresponding limitations as set forth in claim 1 above; therefore, it is rejected under the same subject matter.
Referring to claim 20, Tian et al. teaches a non-transitory computer-storage medium (memory, see Tian et al., Para. 6) comprising instructions that, when executed by one or more processors of a machine, configure the machine to perform operations , which recites the corresponding limitations as set forth in claim 1 above; therefore, it is rejected under the same subject matter.
Claims 2, 3 and 12-13 are rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (U.S. Pat. Pub. 2024/0086464) in view of Christianson et al. (U.S. Pat. Pub. 2002/0120630) as applied to claims 1, 11 and 20 above, and in further view of Dean et al. (U.S. Pat. Pub. 2019/0377807).
As to claim 2, Tian et al. as modified teaches the unified representation being provided in storage and in memory during query processing (the output queue may be stored in a table in a relational database, see Tian et al., Para. 90, an SQL query, that is appropriate for accessing the legacy database, see Christianson et al., Para. 63, wherein the database is a storage and memory).
However, Tian et al. as modified does not explicitly teach a set of structured type fields that include a set of semi-structured typed fields that enables type validation and schema enforcement for the set of structured type fields.
Dean et al. teaches a set of structured type fields that include a set of semi-structured typed fields that enables type validation (The system may determine if a token contains numbers,… The system may determine if a token is alphanumeric,… determine how many characters there are in a token, or if a token fits a certain regular expression,… The system may determine if the token is in a standard field ( e.g., first name, last name, etc.), where the system may determine if the data conforms to the field (e.g., letters conform to a last name field, etc.), see Dean et al., Para. 35) and schema enforcement for the set of structured type fields (mapping the target data in the source fields of the segments to a plurality of target fields of a target schema based at least in part on the characterizing, see Dean et al., Para. 4).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Tian et al. as modified, to have a set of structured type fields that include a set of semi-structured typed fields that enables type validation and schema enforcement for the set of structured type fields, as taught by Dean et al., to significantly reduce the amount of development time needed to map ambiguous, heterogenous data to target schema (Dean et al., Para. 52).
As to claim 3, Tian et al. as modified teaches the unified representation is stored in the memory (the output queue may be stored in a table in a relational database, see Tian et al., Para. 90, an SQL query, that is appropriate for accessing the legacy database, see Christianson et al., Para. 63, wherein the database is a storage and memory), wherein the unified representation enables seamless integration between structured and semi-structured data types through unified SQL interface operations (the output queue may be stored in a table in a relational database, see Tian et al., Para. 90, an SQL query, that is appropriate for accessing the legacy database, see Christianson et al., Para. 63).
Claim 12 is rejected under the same rationale as stated in the claim 2 rejection.
Claim 13 is rejected under the same rationale as stated in the claim 3 rejection.
Claims 4 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (U.S. Pat. Pub. 2024/0086464) in view of Christianson et al. (U.S. Pat. Pub. 2002/0120630) as applied to claims 1, 11 and 20 above, and in further view of Binkert et al. (U.S. Pat. Pub. 2013/0166568).
As to claim 4, Tian et al. as modified does not 3explicitly teach determining that the field contains a JSON null value; determining that the target field type does not support JSON nulls; and converting the JSON null value to a NULL value in the target field type.
However, Binkert et al. teaches determining that the field contains a JSON null value; determining that the target field type does not support JSON nulls (Since ANSI SQ L does not support the same types as JSON, the inferred types are converted into the most specific types seen thus far for the relational view, see Binkert et al., Para. 147); and converting the JSON null value to a NULL value in the target field type (A JSON null is a value, just as the number 9 is a value. In a relation, NULL indicates that there was no value specified. In SQL, nulls are presented as tags<null>:boolean, where the Boolean value is True if the null exists, and NULL otherwise. To simplify the schema for a SQL user, the coordinates<null>column can be omitted if the user does not need to differentiate JSON nulls from SQL nulls, see Binkert et al., Para. 108).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Tian et al. as modified, to have determining that the field contains a JSON null value; determining that the target field type does not support JSON nulls; and converting the JSON null value to a NULL value in the target field type, as taught by Binkert et al., to have high throughput and low cost (Binkert et al., Para. 235).
Claim 14 is rejected under the same rationale as stated in the claim 4 rejection.
Claims 6-10 and 15-19 are rejected under 35 U.S.C. 103 as being unpatentable over Tian et al. (U.S. Pat. Pub. 2024/0086464) in view of Christianson et al. (U.S. Pat. Pub. 2002/0120630) as applied to claims 1, 11 and 20 above, and in further view of Liu et al. (U.S. Pat. Pub. 2024/0126727).
As to claim 6, Tian et al. as modified teaches storing the unified representation as native data types (the output queue may be stored in a table in a relational database, see Tian et al., Para. 90); implementing type coercion rules for the converted field values (a given semi-structured input, the conversion rules control conversion into corresponding structured database output, see Christianson et al., Para. 11).
However, Tian et al. as modified does not explicitly teach
adding internal cast functions to support casting from semi-structured to structured types.
Liu et al. teaches adding internal cast functions to support casting from semi-structured to structured types (a JSON schema may be defined in a "casting mode", which causes values of JSON fields that are defined with an augmentation type to be stored in the storage format of the respective native data type, see Liu et al., Para. 67)
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Tian et al. as modified, to have adding internal cast functions to support casting from semi-structured to structured types, as taught by Liu et al., to improve execution efficiency of database statements that access JSON objects and improve software development productivity (Liu et al., Abstract).
As to claim 7, Tian et al. teaches collecting metadata for the converted field values (collects metadata for a predetermined number of records from semi-structured data, see Tian et al., Para. 60, the metadata collection module 410 may determine a plurality of attribute names (and a plurality of attribute values, if needed) from the predetermined number of records, see Tian et al., Para. 63).
However, Tian et al. as modified does not explicitly teach pushing down extraction expressions to table scans as virtual columns; and performing compile-time optimizations based on the collected metadata for structured type fields.
Liu et al. teaches pushing down extraction expressions to table scans as virtual columns (A more specific scenario for coincident validation involves a JSON casting operator. JSON casting operators may be used to rewrite database statements that assign a non-JASON typed SQL expression to a JSON typed column, where the non-JSON data type may be a string or character data type value constructed as a JSON object. When a DBMS compiles such a database statement, the DBMS casts the SQL expression as a JSON type JSON object by, in effect, rewriting the database statement to include a JSON casting operator that takes as input the SQL expression, see Liu et al., Para. 45); and performing compile-time optimizations based on the collected metadata for structured type fields (A type of compilation optimization is constant folding. Constant folding recognizes and evaluates constant expressions at compile time rather than performing the evaluation at runtime, see Liu et al., Para. 60).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Tian et al. as modified, to have pushing down extraction expressions to table scans as virtual columns; and performing compile-time optimizations based on the collected metadata for structured type fields, as taught by Liu et al., to improve execution efficiency of database statements that access JSON objects and improve software development productivity (Liu et al., Abstract).
As to claim 8, Tian et al. teaches a data structure that maintains type information for semi-structured data as part of the semi-structured data (the metadata collection module 410 may determine a plurality of attribute names (and a plurality of attribute values, if needed) from the predetermined number of records, see Tian et al., Para. 63. Data type of the names (also referred to as attribute names) may be string. Data type of the values (also referred to as attribute values), see Tian et al., Para. 66); and schema information that allows new attributes to be added to semi-structured fields at a subsequent time (At 202, mapper 50 transforms structured data 52 adding corresponding companion columns to the tables to store entity identifiers for the stored entity data, see Christianson et al., Para. 48).
However, Tian et al. as modified does not explicitly teach field definitions that enable type validation during query processing.
Liu et al. teaches field definitions that enable type validation during query processing (JSON schema validation entails traversing the fields of a JSON object and determining whether the field is described by the JSON schema at the path prescribed by the JSON schema and that the data type of the field's value complies with the JSON schema, see Liu et al., Para. 39, FIG. 5 illustrates a query rewrite based on a JSON schema, see Liu et al., Para. 72).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Tian et al. as modified, to have field definitions that enable type validation during query processing, as taught by Liu et al., to improve execution efficiency of database statements that access JSON objects and improve software development productivity (Liu et al., Abstract).
As to claim 9, Tian et al. teaches identifying extractions on Structured type columns (the metadata collection module 410 may determine a plurality of attribute names (and a plurality of attribute values, if needed) from the predetermined number of records, see Tian et al., Para. 63. Data type of the names (also referred to as attribute names) may be string. Data type of the values (also referred to as attribute values), see Tian et al., Para. 66); representing the extractions as virtual columns (the metadata may comprise the attribute names (and the attribute values, if needed). Also, the metadata collection module 410 may determine a number of respective attribute names in the predetermined number of records and include them in the metadata, see Tian et al., Para. 63); retrieving and populating expression properties (EPs) for structured type fields (decomposition module 430 may output the appended set of values (i.e., the first components and the second set of values) based on the structured format, see Tian et al., Para. 89).
However, Tian et al. as modified does not explicitly teach applying EP-based compile-time optimizations to the query processing.
Liu et al. teaches applying EP-based compile-time optimizations to the query processing (A type of compilation optimization is constant folding. Constant folding recognizes and evaluates constant expressions at compile time rather than performing the evaluation at runtime, see Liu et al., Para. 60, DBMS 100 detects that the database statement being compiled assigns a non-JSON type SQL expression to a JSON column, see Liu et al., Para. 52).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Tian et al. as modified, to have applying EP-based compile-time optimizations to the query processing, as taught by Liu et al., to improve execution efficiency of database statements that access JSON objects and improve software development productivity (Liu et al., Abstract).
As to claim 10, Tian et al. teaches; collecting expression properties (EPs) for the virtual columns (decomposition module 430 may output the appended set of values (i.e., the first components and the second set of values) based on the structured format, see Tian et al., Para. 89).
Tian et al. as modified does not explicitly teach generating extraction expressions for structured type fields; pushing the extraction expressions into table scans as virtual columns; performing data-dependent optimizations based on the collected EPs.
Liu et al. teaches generating extraction expressions for structured type fields (DBMS 100 rewrites the database statement to include the JSON casting operator JSON( ) for SQL_expression, see Liu et al., Para. 50); pushing the extraction expressions into table scans as virtual columns (If a JSON schema is defined for the JSON Column, then schema validation pushdown is performed by rewriting the database statement to include the JSON casting operator with an input argument referring to the JSON schema, see Liu et al., Para. 53); performing data-dependent optimizations based on the collected Eps (A type of compilation optimization is constant folding. Constant folding recognizes and evaluates constant expressions at compile time rather than performing the evaluation at runtime, see Liu et al., Para. 60).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Tian et al. as modified, to have generating extraction expressions for structured type fields; pushing the extraction expressions into table scans as virtual columns; performing data-dependent optimizations based on the collected EPs, as taught by Liu et al., to improve execution efficiency of database statements that access JSON objects and improve software development productivity (Liu et al., Abstract).
Claim 16 is rejected under the same rationale as stated in the claim 6 rejection.
Claim 17 is rejected under the same rationale as stated in the claim 7 rejection.
Claim 18 is rejected under the same rationale as stated in the claim 8 rejection.
Claim 19 is rejected under the same rationale as stated in the claim 9 rejection.
Conclusion
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/JAU SHYA MENG/Primary Examiner, Art Unit 2168