U.S. patent application number 12/406875 was filed with the patent office on 2010-09-23 for interpretation and execution of a customizable database request using an extensible computer process and an available computing environment.
Invention is credited to ERIC Friedman, Peter Pawlowski.
Application Number | 20100241893 12/406875 |
Document ID | / |
Family ID | 42738531 |
Filed Date | 2010-09-23 |
United States Patent
Application |
20100241893 |
Kind Code |
A1 |
Friedman; ERIC ; et
al. |
September 23, 2010 |
INTERPRETATION AND EXECUTION OF A CUSTOMIZABLE DATABASE REQUEST
USING AN EXTENSIBLE COMPUTER PROCESS AND AN AVAILABLE COMPUTING
ENVIRONMENT
Abstract
Interpretation and execution of a customizable database request
using an extensible computer process and an available computing
environment is disclosed. In an embodiment, a method includes
generating an interpretation of a customizable database request
which includes an extensible computer process and providing an
input guidance to available processors of an available computing
environment. The method further includes automatically distributing
an execution of the interpretation across the available computing
environment operating concurrently and in parallel, wherein a
component of the execution is limited to at least a part of an
input data. The method also includes automatically assembling a
response using a distributed output of the execution.
Inventors: |
Friedman; ERIC; (Mountain
View, CA) ; Pawlowski; Peter; (Menlo Park,
CA) |
Correspondence
Address: |
Raj Abhyanker, P.C.
1580 West, El Camino Real, Suite 8
Mountain View
CA
94040
US
|
Family ID: |
42738531 |
Appl. No.: |
12/406875 |
Filed: |
March 18, 2009 |
Current U.S.
Class: |
714/2 ;
707/E17.009; 714/E11.023 |
Current CPC
Class: |
G06F 16/24532
20190101 |
Class at
Publication: |
714/2 ;
707/E17.009; 714/E11.023 |
International
Class: |
G06F 17/30 20060101
G06F017/30; G06F 11/07 20060101 G06F011/07 |
Claims
1. A method comprising: generating an interpretation of a
customizable database request which includes an extensible computer
process; providing an input guidance to available processors of an
available computing environment; automatically distributing an
execution of the interpretation across the available computing
environment operating concurrently and in parallel, wherein a
component of the execution is limited to at least a part of an
input data; and automatically assembling a response using a
distributed output of the execution.
2. The method of claim 1, wherein the input guidance is provided to
each of the available processors and is comprised of certain
portions of the input data, and wherein the input guidance is used
to determine which of the available processors are to perform
functions related to the at least the part of the input data.
3. The method of claim 1 further comprising: providing an
information to the extensible computer process about its context in
the customizable database request; and processing an interpretation
of the customizable database request based on the information
provided, wherein the extensible computer process is a developer
provided-computer program, and wherein the information provided
includes at least one of a format of the input data and an output
data, whether the input data and the output data is ordered and in
which form, grouping information, statistics of the input data and
the output data, a distribution information, a length of the input
data and the output data, and a custom parameter.
4. The method of claim 3, wherein the custom parameter is at least
one of a number, a string, a list of numbers of strings, a content
of a file in the available computing environment, and a result of
the customizable database request.
5. The method of claim 1 further comprising post processing an
output of each of the available processors when automatically
assembling the response.
6. The method of claim 5 wherein the post processing includes at
least one database operation including at least one of an
aggregation operation, a sorting operation, and an invocation of
another extensible computer process.
7. The method of claim 1 further comprising pre-processing an input
of each of the available processors when providing the input
guidance to the available processors.
8. The method of claim 1 wherein the available computing
environment is comprised of at least two servers.
9. The method of claim 1, wherein the customizable database request
specifies the input data for the extensible computer process.
10. The method of claim 7, wherein the input data is structured in
a form comprising at least one of a database table and an output of
a different database query.
11. The method of claim 7, wherein the input data is unstructured
in a form comprising a content of at least one file in a computing
environment.
12. The method of claim 1, further comprising: detecting a fault in
the execution of the interpretation; and automatically rectifying
an output effect of the fault.
13. The method of claim 12, wherein rectifying the output effect of
the fault includes at least one of reprocessing an operation,
excluding a corrupted data, and logging the corrupted data.
14. The method of claim 1, wherein the customizable database
request is comprised of at least one of a predetermined function, a
developer created function, and an analyst created function.
15. A system comprising: a query planning module to generate an
interpretation of a database request which includes an extensible
computer process; a parallelization module to provide an
information to available processors of an available computing
environment and to automatically distribute an execution of the
interpretation across the available computing environment operating
concurrently and in parallel, wherein a component of the execution
is limited to at least a part of an input data; and a response
organization module to automatically assemble a response using a
distributed output of the execution.
16. The system of claim 15, wherein the information is used to
provide each of the available processors certain portions of the
input data, and to determine which of the available processors are
to perform functions related to the at least the part of the input
data.
17. The system of claim 15 further comprising: a reference module
to provide an extensible computer process information about its
context in the database request; and a dynamic interpretation
module to process information that affects the interpretation of
the database request based on the information provided, wherein the
extensible computer process is a developer provided-computer
program, and wherein the information provided includes a format of
the input data and an output data, whether the input data and the
output data is ordered and in which form, grouping information,
statistics of the input data, a distribution information, a length
of the input data and the output data, and custom parameters.
18. The system of claim 17, wherein the custom parameters are at
least one of a number, a string, a list of numbers of strings, a
content of a file in the available computing environment, and a
result of the database request.
19. A method comprising: generating an interpretation of a
customizable database request which includes an extensible computer
process; providing an input guidance to available processors of an
available computing environment, wherein the input guidance
determines which of the available processors are to perform
functions related to the at least a part of an input data;
pre-processing an input of each of the available processors when
providing the input guidance to the available processors;
automatically distributing an analysis phase of the interpretation
across the available computing environment operating concurrently
and in parallel, wherein a component of the analysis phase is
limited to at least a part of the input data; automatically
distributing an additional analysis phase of the interpretation
across the available computing environment; automatically
assembling a response using a distributed output of the additional
analysis phase; and post processing an output of each of the
available processors when automatically assembling the response,
wherein the post processing includes at least one database
operation including at least one of an aggregation operation, a
sorting operation, and an invocation of another extensible computer
process.
20. The method of claim 19 further comprising: providing an
extensible computer process information about its context in the
customizable database request; and processing information that
affects the interpretation of the customizable database request
based on the information provided, wherein the extensible computer
process is a developer provided-computer program, and wherein the
information provided includes at least one of a format of the input
data and an output data, whether the input data and the output data
is ordered and in which form, grouping information, statistics of
the input data, a distribution information, a length of the input
data and the output data, and custom parameters, wherein the custom
parameters are at least one of a number, a string, a list of
numbers of strings, a content of a file in the available computing
environment, and a result of the customizable database request.
Description
FIELD OF TECHNOLOGY
[0001] This disclosure relates generally to interpretation and
execution of a customizable database request using an extensible
computer process and an available computing environment.
BACKGROUND
[0002] A database analyst may seek to request information from a
database but may be prevented from doing so by a lack of an ability
to customize a database query. The database analyst may also be
unable to distribute the processing of the query across a
distributed computational environment, which may include one or
more servers. The database analyst may be restricted to a limited
set of queries that may limit the effectiveness of the analyst's
ability to obtain information from the database. The analyst may
therefore seek data inefficiently using an excessive number of
queries. The data analyst may also be required to transfer the
processed information of the database to a separate process to
analyze the data. The database analyst may therefore be required to
spend an excessive amount of time obtaining information, which may
lead to a delay, an additional cost of the analyst's time, an
additional time for a processor usage, and a greater possibility of
incurring a human made error. The database analyst may ultimately
fail to find a desired information.
SUMMARY
[0003] Interpretation and execution of a customizable database
request using an extensible computer process and an available
computing environment is disclosed. In an aspect, a method includes
generating an interpretation of a customizable database request
which includes an extensible computer process and providing an
input guidance to available processors of an available computing
environment. The method further includes automatically distributing
an execution of the interpretation across the available computing
environment operating concurrently and in parallel, wherein a
component of the execution is limited to at least a part of an
input data. The method also includes automatically assembling a
response using a distributed output of the execution.
[0004] The input guidance may be provided to each of the available
processors and may be comprised of certain portions of the input
data. The input guidance may be used to determine which of the
available processors are to perform functions related to the at
least the part of the input data. The method may further include
providing an information to the extensible computer process about
its context in the customizable database request, and processing an
interpretation of the customizable database request based on the
information provided. The extensible computer process may be a
developer provided-computer program, and the information provided
may include at least one of a format of the input data and an
output data, whether the input data and the output data is ordered
and in which form, grouping information, statistics of the input
data and the output data, a distribution information, a length of
the input data and the output data, and a custom parameter.
[0005] The custom parameter may be at least one of a number, a
string, a list of numbers of strings, a content of a file in the
available computing environment, and a result of the customizable
database request. The method may further include post processing an
output of each of the available processors when automatically
assembling the response. The post processing may include at least
one database operation including at least one of an aggregation
operation, a sorting operation, and an invocation of another
extensible computer process.
[0006] The method may further include pre-processing an input of
each of the available processors when providing the input guidance
to the available processors. The available computing environment
may be comprised of at least two servers. The customizable database
request may specify the input data for the extensible computer
process. The input data may be structured in a form comprising at
least one of a database table and an output of a different database
query.
[0007] The input data may be unstructured in a form comprising a
content of at least one file in a computing environment. The method
may further include detecting a fault in the execution of the
interpretation, and automatically rectifying an output effect of
the fault. Rectifying the output effect of the fault may include at
least one of reprocessing an operation, excluding a corrupted data,
and logging the corrupted data. The customizable database request
may be comprised of at least one of a predetermined function, a
developer created function, and an analyst created function.
[0008] In another aspect, a system may include a query planning
module to generate an interpretation of a database request which
includes an extensible computer process, and a parallelization
module to provide an information to available processors of an
available computing environment and to automatically distribute an
execution of the interpretation across the available computing
environment operating concurrently and in parallel. A component of
the execution may be limited to at least a part of an input data.
The system may further include a response organization module to
automatically assemble a response using a distributed output of the
execution.
[0009] The information may be used to provide each of the available
processors certain portions of the input data, and to determine
which of the available processors are to perform functions related
to the at least the part of the input data. The system may include
a reference module to provide an extensible computer process
information about its context in the database request. The system
may include a dynamic interpretation module to process information
that affects the interpretation of the database request based on
the information provided, wherein the extensible computer process
is a developer provided-computer program.
[0010] The information provided may include a format of the input
data and an output data, whether the input data and the output data
is ordered and in which form, grouping information, statistics of
the input data, a distribution information, a length of the input
data and the output data, and custom parameters. The custom
parameters may be at least one of a number, a string, a list of
numbers of strings, a content of a file in the available computing
environment, and a result of the database request.
[0011] In yet another aspect, a method includes generating an
interpretation of a customizable database request which includes an
extensible computer process, and providing an input guidance to
available processors of an available computing environment. The
input guidance determines which of the available processors are to
perform functions related to the at least a part of an input data.
The method further includes pre-processing an input of each of the
available processors when providing the input guidance to the
available processors, and automatically distributing an analysis
phase of the interpretation across the available computing
environment operating concurrently and in parallel. A component of
the analysis phase is limited to at least a part of the input
data.
[0012] The method further includes automatically distributing an
additional analysis phase of the interpretation across the
available computing environment, and automatically assembling a
response using a distributed output of the additional analysis
phase. The method also includes post processing an output of each
of the available processors when automatically assembling the
response. The post processing includes at least one database
operation including one or more of an aggregation operation, a
sorting operation, and an invocation of another extensible computer
process.
[0013] The method may include providing an extensible computer
process information about its context in the customizable database
request, and processing information that affects the interpretation
of the customizable database request based on the information
provided. In the aspect, the extensible computer process is a
developer provided-computer program, and the information provided
includes at least one of a format of the input data and an output
data, whether the input data and the output data is ordered and in
which form, grouping information, statistics of the input data, a
distribution information, a length of the input data and the output
data, and custom parameters. The custom parameters are one or more
of a number, a string, a list of numbers of strings, a content of a
file in the available computing environment, and a result of the
customizable database request.
[0014] Other aspects and example embodiments are provided in the
drawings and the detailed description that follows.
BRIEF DESCRIPTION OF THE VIEWS OF DRAWINGS
[0015] Example embodiments are illustrated by way of example and
not limitation in the figures of the accompanying drawings, in
which like references indicate similar elements and in which:
[0016] FIG. 1 is a system view illustrating processing of a
customizable database query using a developer extensible operation
and an available computing environment, according to one
embodiment.
[0017] FIG. 2 is an exploded view of the available computing
environment, according to one embodiment.
[0018] FIG. 3 is an exploded view of a query planning module,
according to one embodiment.
[0019] FIG. 4 is an exploded view of a monitoring module, according
to another embodiment.
[0020] FIG. 5 is an illustration of processing input data to
generate a query response, according to another embodiment.
[0021] FIG. 6 is a system view of an alternate embodiment of
processing of a customizable database query using a developer
extensible operation and an available computing environment.
[0022] FIG. 7 is an illustration of processing input data to
generate a query response, according to an alternate
embodiment.
[0023] FIG. 8 is a diagrammatic system view of a data processing
system in which any of the embodiments disclosed herein may be
performed, according to one embodiment.
[0024] FIG. 9 is a process flow of interpreting and executing a
customizable database request, according to one embodiment.
[0025] FIG. 10 is a process flow of automatically distributing an
analysis phase and an additional analysis phase of the
interpretation of a customizable database request across the
available computing environment, according to one embodiment.
[0026] Other features of the present embodiments will be apparent
from the accompanying drawings and from the detailed description
that follows.
DETAILED DESCRIPTION
[0027] Interpretation and execution of a customizable database
request using an extensible computer process and an available
computing environment is disclosed. Although the present
embodiments have been described with reference to specific example
embodiments, it will be evident that various modifications and
changes may be made to these embodiments without departing from the
broader spirit and scope of the various embodiments.
[0028] FIG. 1 is a system view illustrating processing of a
customizable database query using a developer extensible operation
and an available computing environment, according to one
embodiment. In particular, FIG. 1 illustrates an extensible
computer process 100, a query planning module 102, an analysis
phase 104, an additional analysis phase 106A-N, an available
computing environment 112, a monitoring module 114, a response 116,
a user interface 118, an analyst 120, a developer 122, a
customizable database request 124, and servers 126.
[0029] FIG. 1 illustrates an analyst 120 providing a customizable
database request 124 to a extensible computer process 100. The
analyst 120 may be a database analyst who is familiar with SQL
(e.g., a Structured Query Language). SQL may be a database computer
language designed for the retrieval and management of data in
relational database management systems (RDBMS), database schema
creation and modification, and database object access control
management. The analyst 120 may have limited knowledge of other
programming languages, and may have a substantially limited ability
to create programs, to modify software, and to manage software
distributed across multiple processors. The analyst 120 may be
tasked with searching for data rather than developing programs.
[0030] The customizable database request 124 may consist of a SQL
instruction and/or it may be written in any programming language.
The customizable database request 124 may be customized to include
a function (e.g., a nested SQL command, a mathematical equation, a
variable, a standard deviation, etc.). The function may be created
by the analyst 120, the developer 122, and/or it may be a
predetermined function. The function may be customized to search
multiple records at once, to retrieve and/or manipulate data in
multiple forms (e.g., tables, images, unstructured data 584, text
files, programs, sound files, photos, etc.). The function may
access data in one form and generate data in another form. The
customizable database request 124 may further specify an input data
510 for the extensible computer process 100.
[0031] The customizable database request 124 may allow the process
to be scaled in accordance with a changing system hardware and/or
performance of a system. The function may allow user-implemented
procedural code to be uploaded to a database and executed at each
node of a system. A user (e.g., an analyst 120, a developer 122,
etc.) may provide code that may operate on individual rows and/or
on groups of rows. The customizable database request 124 may take
in input using a set of rows in a table (e.g., a persistent table
in a database, the output of a SQL SELECT statement and/or the
output of another function, etc.). The customizable database
request 124 may result in an output that includes a relation of a
set of rows (e.g., an output unrelated to the input.) The
customizable database request 124 and/or a function of the
customizable database request 124 may be placed into a SQL SELECT
query and/or any other query as though it were itself a table. This
integration with SQL may allow for composing SQL and procedural
code invocations in any form and shape. The code may be written in
Java, Python, and/or any other language.
[0032] In an embodiment, the customizable database request 124 may
include a function that is written in Java that is then invoked as
part of a SQL query statement. The function may convert sets of
rows to sets of rows. The function may be parallelized to operate
on rows across multiple nodes simultaneously. The function may be
invoked on arbitrary sets of rows and/or rows grouped together by a
PARTITION BY clause. Within a partition, rows may be further sorted
using an ORDER BY clause.
[0033] In an embodiment, a function may split strings into words.
In the embodiment, the function may be invoked once for every row
in an input table. The function may include Java procedural code
that takes each document and emits a row for each word. The
function may define a column that appears in its output rows. In
another embodiment, a function may be created to compute the 10
most-frequently occurring words in a body of text using the
function to split strings into words.
[0034] In yet another embodiment, a function of the customizable
database request 124 may perform sessionization by mapping each
click in a clickstream to a unique session identifier. The function
may define a session as a sequence of clicks by a particular user
where no more than n seconds pass between successive clicks (e.g.,
if a click from a user isn't seen for n seconds, a new session is
started. The function may use a userid and/or a timestamp
attribute. The function may include as parameters the name of the
timestamp attribute, the number of seconds between clicks that
results in starting a new session. A clickstream table may be
partitioned by userid, and partition tuples may be sequenced by
timestamp. The sessionize function may then be invoked against each
of the ordered partitions and/or emit the input tuples with an
appropriate sessionid added.
[0035] The customizable database request 124 may be received by an
extensible computer process 100, which may be designed to take into
consideration future growth by allowing the addition and/or
modification of functionality. The addition of new functionality
and/or the modification of existing functionality may be
accomplished with limited impact to existing system functions. A
developer 122 may be familiar with a type of programming involving
database analysis, query modification, and/or data searches. The
developer 122 may possess limited knowledge regarding programs to
distribute an analysis across multiple computing systems. The
developer 122 may support and/or design software for the analyst
120. The developer 122 may adapt the extensible computer process
100 to add new functions, modify existing functions, and/or add
additional language ability to the software.
[0036] The extensible computer process 100 may communicate with a
query planning module 102 to generate a query interpretation of the
customizable database request 124. The query interpretation may be
formatted to be distributable (e.g., separated into individual
tasks for separate processes, etc.). The query interpretation may
convert the customizable database request 124 from any computer
language (e.g., a machine-readable artificial language designed to
express computations that can be performed by a machine, C++, SQL,
Perl, Java, Prolog, etc.) into a preferred programming language.
The query interpretation may automatically format the customizable
database query to be processed using a distributable, multiphase
analysis.
[0037] The query planning module 102 may generate an interpretation
(e.g., the query interpretation) of the customizable database
request, which may include an extensible computer process. The
query planning module 102 may optimize the analysis phase and/or
the additional analysis phase using a parameter (e.g., an expected
output file size, an input file format, a table dimension, etc.).
The query planning module may provide an input guidance to
available processors of the available computing environment. The
input guidance may include certain portions of the input data, and
the input guidance may be used to determine which of the available
processors are to perform functions related to different parts of
the input data.
[0038] The query planning module 102 may use the parameter to
allocate a system resource (e.g., memory, power supply output,
processor usage, a number of servers applied, a sequence of
processors used, a timing of processes analyzed, etc.). The
allocation of a system resource may include a distribution of
processes across an available computing environment 112, a
selection of a type of analysis to apply, and/or a selection of
input data to review. The execution of the interpretation may be
automatically distributed across an available computing environment
operating concurrently and in parallel, and a component of the
execution may be limited to a part of the input data. The part of
the input data may be a subset of the input data, which may allow
the execution to be divided into separate tasks to be processed by
different machines.
[0039] The available computing environment 112 (e.g., networked
processors, virtual machines, multiple processors of a server,
multiple servers 126A-N and 128A-N, etc.) may be comprised of
servers that are and/or will be available to process data. The
available computing environment 112 may be better illustrated in
FIG. 2.
[0040] The query interpretation may be dynamically determined based
on a context (e.g., a repeated pattern of requested information, an
association between an analyst's customizable database request 124
and an input data 510, an available input data 510, etc.). The
context of the customizable database request 124 may include the
type of requested information, the language of the request, and/or
the expected response 116. For example, if the analyst's request
includes a name and address, the analysis phase 104 and/or the
additional analysis phase 106A-N may be adjusted to provide a
response 116 that includes GPS coordinates (e.g., latitude and/or
longitude, etc.). In another embodiment, the query interpretation
may automatically provide alternate responses based on a variation
of the requested parameters, such as by expanding or contracting a
search parameter to provide alternate responses, varying search
parameters, and searching for peak values.
[0041] The interpretation of the customizable database request
generated by the query planning module 102 may be processed based
on a contextual information provided to the extensible computer
process. The extensible computer process may be a developer
provided-computer program. The information provided may include a
format of the input data and the output data, whether the input
data and the output data are ordered and in which form, grouping
information, statistics of the input data and the output data, a
distribution information, a length of the input data and the output
data, and a custom parameter.
[0042] The custom parameter may be a number, a string, and/or a
list of numbers of strings. The custom parameter may further
include a content of a file in the available computing environment,
and/or a result of the customizable database request (e.g., the
response 116).
[0043] The query interpretation generated by the query planning
module 102 may be communicated to an analysis phase 104, which may
be automatically distributed across an available computing
environment 112. The automatic distribution of the query
interpretation may allow separate machines to analyze the query
using portions of an input data 510 simultaneously, in parallel, in
an overlapping sequence, and/or in series.
[0044] The analysis phase 104 may include a component that is
limited to a part of the input data 510. The component may process
a part of a "map" phase of a MapReduce analysis (e.g., a framework
for computing a distributable problem). The component may process a
part of the analysis phase 104 using its part of the input data
510. The analysis phase 104 may also include an additional
component that uses the output of the component to generate an
additional output (e.g., the additional component operates in
series with the component, the additional component uses the output
of the component as one of several inputs, etc.).
[0045] The analysis phase 104 may process the query interpretation
using the input data 510, which may be acquired from the database
108A-N. The input data 510 may include structured data and/or
unstructured data 584, as illustrated in FIG. 5. The input data of
the analysis phase may be generated using a combination of multiple
data sources (e.g., multiple tables, storage devices, etc.). The
portion of the input data used by a component of the analysis phase
104 may also be generated using a combination of multiple data
sources.
[0046] The analysis phase 104 may communicate with a monitoring
module 114 and/or the additional analysis phase 106A-N, which may
be automatically distributed across the available computing
environment (e.g., currently available servers, virtual machines,
processors, etc.). The additional analysis phase 106A-N may access
a greater amount of information that the amount of the input data
510 used by the analysis phase 104. The additional analysis phase
106A-N may operate in parallel, in series, or in any other pattern
with the analysis phase 104.
[0047] The response 116 may be automatically assembled using a
distributed output of the additional analysis phase 106A-N. The
output of the additional analysis phase 106A-N may be distributed
across multiple processors, servers, and/or virtual machines, and a
complete resulting output may require an accumulation of all
distributed parts of the additional analysis phase 106A-N output.
The assembled output may be the response 116. The response 116 may
be displayed through a user interface (e.g., a web browser, a
terminal, a PC, a server, a monitor, etc.).
[0048] The monitoring module 114 may observe the input data 510
provided to the analysis phase 104, the available computing
environment 112, the input to the additional analysis phase 106A-N,
the processing of information by the additional analysis phase
106A-N, and the assembled response 116. The monitoring module 114
may manage the automatic distribution of the analysis phase 104
and/or the additional analysis phase 106A-N across the available
computing environment 112. The monitoring module 114 may assemble
the distributed output of the additional analysis phase 106A-N to
generate the response 116.
[0049] The monitoring module 114 may detect a fault (e.g., an
exception, a hardware failure, a system crash, a processor failure,
a data error, a processing error, etc.) in the analysis phase 104
and/or the additional analysis phase 106A-N. The monitoring module
114 may automatically rectify an output effect (e.g., a data
corruption, a propagating data error, a system failure, etc.) of
the fault. The rectification may include one or more of
reprocessing an operation (e.g., a component of the analysis phase
104, the additional analysis phase 106A-N, etc.), excluding a
corrupted data, and/or logging a corrupted data. The rectification
may include isolating a fault generating process and/or hardware
mechanism. The monitoring module 114 may rectify an output effect
automatically (e.g., without intervention by the developer 122
and/or analyst 120).
[0050] FIG. 2 is an exploded view of the available computing
environment 112 illustrated in FIG. 1, according to one embodiment.
In particular, FIG. 2 illustrates the available computing
environment 112, the servers 126A-N, and the databases 108A-N,
according to one embodiment. The available computing environment
112 may include one or more servers that are currently or will be
open to process information within a preferred time frame. The
servers 126A-N of the available computing environment 112 may be
comprised of one or more separate servers, virtual machines, client
devices, and/or separate processors of a single server. The servers
126A-N may communicate with one or more databases (e.g., databases
108A-N), which may be included within the available computing
environment 112. The servers 126A-N and the databases 108A-N may
communicate with each other via a LAN, a WAN, a MAN, and/or any
other network arrangement. In addition, the databases 108A-N may
include direct attached storage devices, volatile and/or
non-volatile memory.
[0051] FIG. 3 is an exploded view of the query planning module,
according to one embodiment. In particular, FIG. 3 includes the
query planning module 102, an optimization module 330, a SQL
instruction module 332, a dynamic interpretation module 334, a
function module 336, a developer operation module 338, a
translation module 340, and a reference module 342.
[0052] The query planning module 102 may include multiple modules
to perform various functions. For example, the optimization module
330 may optimize the analysis phase 104 and/or the additional
analysis phase 106A-N using a parameter included with the
customizable data request. The parameter may include a prediction
and/or expectation regarding the response 116 (e.g., an output
memory requirement, a number of generated responses, a range of
response outputs, a type of input data 510, etc.). The SQL
instruction module 332 may interpret a SQL command, a nested SQL
instruction, etc.
[0053] The dynamic interpretation module 334 may dynamically
determine a query interpretation of the customizable database
request 124 based on a context (e.g., a scope and/or format of the
customizable database request 124, an aspect of the input data 510,
the available computing environment, etc.). The analysis may be
dynamically altered in accordance with the query
interpretation.
[0054] The function module 336 may alter the query interpretation
based on a function (e.g., a predetermined function, an analyst
and/or developer created function, etc.). The function may be an
equation, a programming command, a sequence of commands, etc. The
developer operation module 338 may generate the query
interpretation based on an operation added and/or modified by a
developer in the extensible computer process 100. The translation
module 340 may generate the query interpretation by translating the
customizable database request 124 from any language (e.g., a
computer programming language such as SQL, Java, dBase, and/or a
human language such as Indonesian, Russian, Spanish, and/or
Chinese). The reference module 342 may provide an extensible
computer process information about its context in the database
request.
[0055] FIG. 4 is an exploded view of the monitoring module,
according to another embodiment. In particular, FIG. 4 illustrates
the monitoring module 114, a detection module 450, a rectification
module 452, a parallelization module 454, an additional
parallelization module 456, and a response organization module
458.
[0056] The detection module 450 may observe an input and/or an
output of the analysis phase 104, the servers 126A-N, and the
available computing environment 112, the additional analysis phase
106A-N. The detection module 450 may also observe the operation and
transmitted data of the database 108A-N, the query planning module,
and/or the extensible computer process 100. The detection module
450 may automatically detect a fault in the analysis phase 104
and/or the additional analysis phase 106A-N.
[0057] The rectification module 452 may automatically rectify an
output effect (e.g., a process failure, a system crash, a corrupted
data, a propagating failure, etc.) of the fault. The automatic
rectification may include an isolation of the fault generating
mechanism (e.g., a process, a server, a component, etc.). The
automatic rectification may include re-executing an interrupted
process (e.g., the analysis phase 104, the component, the
additional analysis phase 106A-N, etc.). The automatic
rectification may include logging the fault and/or the corrupted
data. The rectified data may be excluded (e.g., from a query
response, a repeated analysis phase 104, etc.).
[0058] The parallelization module 454 may automatically distribute
the analysis phase of the query interpretation across an available
computing environment. The additional parallelization module 456
may automatically distribute the additional analysis phase of the
query interpretation across the available computing environment.
The parallelization module 454 and/or the additional
parallelization module 456 may consider a number of processors
available, the number of analyses to be performed, and/or the
sequence of the distributed processes.
[0059] The response organization module 458 may automatically
assemble the response 116 using the distributed output of the
additional analysis phase. The response organization module 458 may
wait for a completion of all necessary processes prior to
assembling the response 116. The response organization module 458
may further post process an output of each of the available
processors when automatically assembling the response. The post
processing may include a database operation, such as an aggregation
operation, a sorting operation, and/or an invocation of a separate
extensible computer process (e.g., an external program, a developer
created function, a third-party software, etc.).
[0060] FIG. 5 is an illustration of processing input data to
generate a query response, according to another embodiment. In
particular, FIG. 5 illustrates the analysis phase 104, the
additional analysis phase 106, the input data 510, the response
116, a component 560, an additional component 562, a table 564,
text 566, an object 568, an audio file 570, a video file 572, an
output table 574, an output text 576, an output object 578, an
audio file 580, an output video file 582, and an unstructured data
584.
[0061] FIG. 5 illustrates a variety of types and forms that may be
taken by the input data 510 and/or the response 116. The input data
510 may include the table 564, the text 566, the object 568, the
audio file 570, and/or the video file 572. The input data may be
structured in a form including a database table and/or an output of
a different database query. The response 116 may include the output
table 574, the output text 576, the output object 578, the output
audio file 580, and/or the output video file 582. The table 564
and/or the output table 574 may be structured data. The text 566,
the object 568, the audio file 570, the video file 572, the output
text 576, the output object 578, the output audio file 580, and/or
the output video file 582 may be unstructured data 584. The input
data 510 may be unstructured in a form including a content of at
least one file in a computing environment. The unstructured data
584 may include a mix of data types, including images and audio
files, text, programs, and/or word processing files.
[0062] The input data 510 may be communicated to the analysis phase
104, which may process the data in the component 560 and/or the
additional component 562. The output of the analysis phase 104 may
be received by the additional analysis phase 106A-N, which may
generate the response 116. The additional analysis phase 106A-N may
consist of one or more phases. The response 116 may be formed of
the same and/or a different data type from the input data 510.
[0063] FIG. 6 is a system view of an alternate embodiment of
processing of a customizable database query using a developer
extensible operation and an available computing environment 112. In
particular, FIG. 6 illustrates the query planning module 102, the
analysis phase 104, the additional analysis phase 106, the database
108, the input data 510, the monitoring module 114, the response
116, the analyst 120, the developer 122, M 686A-C, R 688A-B, and
intermediate files 690.
[0064] The query planning module 102 may receive a customizable
database request 124 from the analyst 120. The developer 122 may
contribute to and/or modify the customizable database request 124.
The query planning module 102 may communicate a query
interpretation to the analysis phase 104. The analysis phase 104
may receive an input data 510 from the database 108. The input data
510 may be divided into split 0-4. The analysis phase may include
multiple components M 686A-C. The additional analysis phase 106 may
include the R 688A-B. The M 686A-C may each represent a map
operation performed on a limited data input (e.g., split 0 and 1,
split 2 and 4, split 3, etc.). The M 686A-C may generate
intermediate files 690, which may be communicated to the additional
analysis phase 106. The R 688A-B may represent reduce operations in
which the output of the map phases are accessible by each of the
reduce operations. The R 688A-B of the additional analysis phase
106 may produce output file 0-1 (e.g., the response 116).
[0065] FIG. 7 is an illustration of processing input data to
generate a response, according to an alternate embodiment. In
particular, FIG. 7 illustrates the input data 510, the analysis
phase 104, the additional analysis phase 106, the response 116, the
developer 122, the M 686A-B and the R 688A-B.
[0066] The input data 510 may include two text files (e.g., the
dog, the cat). The analysis phase 104 may separate the text files
into separate parts (e.g., the, dog, the, cat, etc.). The output of
the operations M 686A-B may be automatically redistributed to the
parts of the additional analysis phase 106. The outputs of the
operations M 686A-B may be sorted and/or categorized. The
operations of the additional analysis phase, R 688A-B may form the
response 116. The query response may include a count of each word
(e.g., 1 "cat," 1 "dog," 2 "the," etc.). The M 686A-B may each be
limited to a part of the input data 510. The R 688A-B may be
capable of accessing all outputs of the analysis phase 104.
[0067] The developer 122 may customize and/or affect the operations
(e.g., the M 686A-B, the R 688A-B, etc.) while the distribution of
the analysis phase 104 and/or the additional analysis phase 106 are
automatically handled.
[0068] FIG. 8 is a diagrammatic system view of a data processing
system in which any of the embodiments disclosed herein may be
performed, according to one embodiment. Particularly, the
diagrammatic system view 800 of FIG. 8 illustrates a processor 802,
a main memory 804, a static memory 806, a bus 808, a video display
810, an alpha-numeric input device 812, a cursor control device
814, a drive unit 816, a signal generation device 818, a network
interface device 820, a machine readable medium 822, instructions
824, and a network 826, according to one embodiment.
[0069] The diagrammatic system view 800 may indicate a personal
computer and/or the data processing system in which one or more
operations disclosed herein are performed. The processor 802 may be
a microprocessor, a state machine, an application specific
integrated circuit, a field programmable gate array, etc. (e.g.,
Intel.RTM. Pentium.RTM. processor). The main memory 804 may be a
dynamic random access memory and/or a primary memory of a computer
system.
[0070] The static memory 806 may be a hard drive, a flash drive,
and/or other memory information associated with the data processing
system. The bus 808 may be an interconnection between various
circuits and/or structures of the data processing system. The video
display 810 may provide graphical representation of information on
the data processing system. The alpha-numeric input device 812 may
be a keypad, a keyboard and/or any other input device of text
(e.g., a special device to aid the physically handicapped).
[0071] The cursor control device 814 may be a pointing device such
as a mouse. The drive unit 816 may be the hard drive, a storage
system, and/or other longer term storage subsystem. The signal
generation device 818 may be a bios and/or a functional operating
system of the data processing system. The network interface device
820 may be a device that performs interface functions such as code
conversion, protocol conversion and/or buffering required for
communication to and from the network 826. The machine readable
medium 822 may provide instructions on which any of the methods
disclosed herein may be performed. The instructions 824 may provide
source code and/or data code to the processor 802 to enable any one
or more operations disclosed herein.
[0072] FIG. 9 is a process flow of interpreting and executing a
customizable database request, according to one embodiment. In
operation 902, an interpretation of a customizable database request
may be generated (e.g., using the translation module 340 and/or the
query planning module 102), which may include an extensible
computer process. In operation 904, an input guidance may be
provided to available processors of an available computing
environment 112. In operation 906, an input of each of the
available processors may be pre-processed (e.g., using the query
planning module 102) when providing the input guidance to the
available processors. In operation 908, an information may be
provided to the extensible computer process about its context in
the customizable database request (e.g., using the dynamic
interpretation module 334 and/or the reference module 342). In
operation 910, an interpretation of the customizable database
request may be processed (e.g., using the query planning module
102) based on the information provided. In operation 912, an
execution of the interpretation may be automatically distributed
(e.g., using the analysis phase 104) across the available computing
environment operating concurrently and in parallel (e.g., using the
reference module 342). In operation 914, a fault may be detected
(e.g., using the detection module 450 of the monitoring module 114)
in the execution of the interpretation. In operation 918, a
response may be automatically assembled (e.g., by the response
organization module 458) using a distributed output of the
execution. In operation 920, an output of each of the available
processors may be post processed (e.g., by the response
organization module 458) when automatically assembling the
response.
[0073] FIG. 10 is a process flow of automatically distributing an
analysis phase and an additional analysis phase of the
interpretation of a customizable database request across the
available computing environment, according to one embodiment. In
operation 1002, an interpretation of a customizable database
request which includes an extensible computer process may be
generated (e.g., using the SQL instruction module 332, the
translation module 340, and/or the optimization module 330 of the
query planning module 102). In operation 1004, an input guidance
may be provided to available processors of an available computing
environment. In operation 1006, an extensible computer process
information may be provided information about its context in the
customizable database request (e.g., using the reference module
342). In operation 1008, an information may be processed (e.g.,
using the dynamic interpretation module 334) that affects the
interpretation of the customizable database request based on the
information provided. In operation 1010, an input of each of the
available processors may be pre-processed when providing the input
guidance to the available processors. In operation 1012, an
analysis phase of the interpretation may be automatically
distributed (e.g., using the parallelization module 454) across the
available computing environment operating computing environment
operating concurrently and in parallel. In operation 1014, an
additional analysis phase of the interpretation may be
automatically distributed (e.g., using the additional
parallelization module 456) across the available computing
environment. In operation 1016, an output of each of the available
processors may be post processed when the response is automatically
assembled (e.g., using the response organization module 458).
[0074] Although the present embodiments have been described with
reference to specific example embodiments, it will be evident that
various modifications and changes may be made to these embodiments
without departing from the broader spirit and scope of the various
embodiments. For example, the various devices, modules, analyzers,
generators, etc. described herein may be enabled and operated using
hardware circuitry (e.g., CMOS based logic circuitry), firmware,
software and/or any combination of hardware, firmware, and/or
software (e.g., embodied in a machine readable medium). For
example, the various structures and methods may be embodied using
transistors, logic gates, and electrical circuits (e.g.,
application specific integrated (ASIC) circuitry and/or in Digital
Signal Processor (DSP) circuitry).
[0075] Particularly, the extensible computer process 100, the query
planning module 102, the analysis phase 104, the additional
analysis phase 106A-N, the monitoring module 114, the user
interface 118, the optimization module 330, the SQL instruction
module 332, the dynamic interpretation module 334, the function
module 336, the developer operation module 338, the translation
module 340, the reference module 342, the detection module 450, the
rectification module 452, the parallelization module 454, the
additional parallelization module 456, the response organization
module 458, the component 560, the additional component 562, the M
686A-C, and the R 688A-B of FIGS. 1-10 may be enabled using
software and/or circuitry.
[0076] In addition, it will be appreciated that the various
operations, processes, and methods disclosed herein may be embodied
in a machine-readable medium and/or a machine accessible medium
compatible with a data processing system (e.g., a computer system),
and may be performed in any order (e.g., including using means for
achieving the various operations). Accordingly, the specification
and drawings are to be regarded in an illustrative rather than a
restrictive sense.
* * * * *