Operators for constants in aggregated formulas

In one embodiment, a method receives a query for analyzing data in a database. The method then determines a constant in the query and determines an operator applied to the constant in the query. The operator explicitly controls a behavior of the constant. The constant is represented as a scalar representation in the query instead of as a vectorial representation where the constant would have been used as the vectorial representation without the use of the operator due to a rule governing use of constants. Then, the method performs a calculation for the query to determine a query result using the constant as the scalar representation.

BACKGROUND

When analyzing data stored in a database, due to the way the database rules are formulated, a user may not receive the expected results that the user desires for a query. In one example, a user may use a constant in a formula of the query. A constant is a value that does not change when calculating the formula with different sets of operands. The database rules define an implicit behavior of how the constant is handled in the formula. For example, the database rules may determine that a constant behaves like a vector if certain database rules are met based on the formula. However, if the certain database rules are not met, then the constant may behave like a scalar. The scalar representation may use less computing resources than the vectorial representation. This is because the scalar representation does not have its own data representation. That is, the scalar value only exists when it is needed. For example, if the formula calculates the average revenue for a product multiplied by a constant for each month of the year, the constant is needed only when a value for a month exists. That is, if the value for a month is NULL, then the constant is not needed. However, the vectorial representation represents the constant for all values for a component of the formula and is needed when the formula result is aggregated again. For example, if a formula is the average revenue for a product added to a constant for each month of the year, then the vectorial representation of a constant is used to include the constant value for all values of the calendar month.

SUMMARY

In one embodiment, a method receives a query for analyzing data in a database. The method then determines a constant in the query and determines an operator applied to the constant in the query. The operator explicitly controls a behavior of the constant. The constant is represented as a scalar representation in the query instead of as a vectorial representation where the constant would have been used as the vectorial representation without the use of the operator due to a rule governing use of constants. Then, the method performs a calculation for the query to determine a query result using the constant as the scalar representation.

In one embodiment, a non-transitory computer-readable storage medium contains instructions, that when executed, control a computer system to be configured for: receiving a query for analyzing data in a database; determining a constant in the query; determining an operator applied to the constant in the query, wherein the operator explicitly controls a behavior of the constant; representing the constant as a scalar representation in the query instead of as a vectorial representation, wherein the constant would have been used as the vectorial representation without the use of the operator due to a rule governing use of constants; and performing a calculation for the query to determine a query result using the constant as the scalar representation.

In one embodiment, an apparatus includes: one or more computer processors; and a non-transitory computer-readable storage medium comprising instructions, that when executed, control the one or more computer processors to be configured for: receiving a query for analyzing data in a database; determining a constant in the query; determining an operator applied to the constant in the query, wherein the operator explicitly controls a behavior of the constant; representing the constant as a scalar representation in the query instead of as a vectorial representation, wherein the constant would have been used as the vectorial representation without the use of the operator due to a rule governing use of constants; and performing a calculation for the query to determine a query result using the constant as the scalar representation.

DETAILED DESCRIPTION

FIG. 1depicts a simplified system100for performing database operations according to one embodiment. A database server102interacts with a database104. An admin, data modeler, or a solution architect may model metadata in a metadata repository107for database104through a metadata manager106. The metadata may include modeling what operators can be used in formulas in queries. Also, the metadata models the rules that an analytical engine114uses to calculate the results of the formulas in the queries.

A data warehousing engine108extracts and transforms data from sources108, and stores the data in database tables110of database104. Once the data is stored in database tables110, an end user may use a client interface112to access the data. For example, the end user accesses an analytical engine114to perform queries on data stored in database tables110. In one example, analytical engine114may interact with a calculation engine116that can perform additional operations to calculate results for the queries using data stored in database tables110. The results from the queries are then output to the end user through client interface112.

As will be described in more detail below, analytical engine114may evaluate formulas in queries based on operators that explicitly govern the behavior of constants in formulas. For example, a user may associate an operator with a constant in a query. Then, analytical engine114uses explicit behavior rules for the operator to represent the constant when calculating a formula in the query. In one embodiment, the operator may be a scalar (SCAL( )) operator or a vector (VECT( )) operator. The SCAL( ) operator forces the constant to behave like a scalar and the VECT( ) operator forces the constant to behave like a vector.

FIG. 2shows a more detailed example of system100according to one embodiment. As shown, metadata repository107includes rules202that govern how analytical engine114evaluates queries. For example, analytical engine114may calculate formulas within the queries based on rules202. As shown, rules202include implicit behavior rules for constants and explicit behavior rules for constants.

Implicit behavior rules for constants are rules that analytical engine114implicitly follows. That is, based on the context of the formula being calculated, analytical engine114follows the implicit behavior rules to calculate the formula. In one embodiment, analytical engine114evaluates the implicit behavior rules to determine how a constant should behave in the formula, such as if a constant in the formula should be represented as a vectorial representation or a scalar representation. The scalar representation may be where the constant is represented as a single value. The vectorial representation is where the constant is represented by multiple values. For example, if a drill-down into the months of the calendar year is being performed, then a constant value may be represented for each of the calendar months in a vectorial representation.

The explicit behavior rules provide operators that may be used in the formula to explicitly control the behavior of the constant. For example, the operators may control the behavior of the constant to be a vectorial representation or a scalar representation. As discussed above, scalar operators and vector operators are provided. When the scalar and vector operators are used in the formula, analytical engine114controls the constant based on the operator used and does not evaluate the implicit behavior rules to determine how to represent the constant. Rather, if a formula defines the constant using the scalar operator, then analytical engine114represents the constant as the scalar representation. Also, if the vector operator is used, analytical engine114represents the constant as a vectorial representation.

FIG. 3depicts a simplified flowchart300of a method for evaluating the behavior of constants according to one embodiment. At302, analytical engine114receives a query. At304, analytical engine114evaluates a formula in the query to determine a constant is found in the formula. Due to a constant being found in the formula, analytical engine114needs to determine how the constant should be represented. At306, analytical engine114determines if an explicit behavior operator is associated with the constant. For example, the SCAL( ) operator or the VECT( ) operator may have been associated with the constant in the formula.

At308, if one of the explicit behavior operators is associated with the constant, analytical engine114controls the behavior of the constant explicitly based on the operator. For example, if the SCAL( ) operator is associated with the constant, then analytical engine114represents the constant as a scalar value. Also, if the VECT( ) operator is associated with the constant, then analytical engine114represents the constant as a vector.

If an explicit behavior operator is not associated with the constant, at310, analytical engine114evaluates the query based on implicit constant behavior rules to determine how to represent the constant. For example, the query is evaluated to determine if the constant should behave like a vector or a scalar. The evaluation of implicit behavior rules will be described in more detail below.

At312, analytical engine114represents the constant in a data representation for the query. For example, if the constant is being represented as a scalar value, then analytical engine114represents the value as a scalar value. However, if the constant is being represented as a vector, analytical engine114represents the constant as a vectorial representation. In this case, analytical engine114may store values for constant for each component of a drill down. Also, analytical engine114extracts any other data that is needed for calculating the formula found in the query.

At314, analytical engine114performs the calculation of the query using the constant. At316, analytical engine114outputs a result for the query. For example, analytical engine114may output a result for the query to the user that submitted the query.

Before describing the implicit behavior rules, aggregation and the use of constants in aggregations will be described.

Aggregation

Analytical engine114may define and calculate formulas with one or more exception aggregation reference characteristics. The input data for these formulas is implicitly aggregated up to the granularity or grouping level the formula calculation requires, and then the formula is calculated to determine formula results. Afterwards, the formula results are then aggregated over the remaining exception aggregation reference characteristics of the formula. The term characteristic may also be referred to as a dimension and the term key figure as used herein may often be referred to as a measure. The following summarizes aggregation in analytical engine114.

FIG. 4depicts a simplified flowchart400that shows the steps of aggregation according to one embodiment. At402, analytical engine114performs standard aggregation. Standard aggregation may be performed with the options of SUM, MIN, and MAX.

At404, if exception aggregation is set up, analytical engine114performs the exception aggregation after the standard aggregation. Exception aggregation includes options such as SUM (default), MIN, MAX, AVG, FIRST, LAST, NOP, COUNT, STANDARD DEVIATION, VARIANCE, etc.

At406, analytical engine114performs the formula calculation if a formula was defined. After the formula calculation, at408, analytical engine114may execute exception aggregation upon the result of the calculated formula. This may be the same step as the exception aggregation executed before, but the formula exception aggregation operates on the formula results. As will be discussed below, the SCAL( ) and VECT( ) operators may be used in exception aggregated formulas in which a result of an aggregation is aggregated again.

Constant Processing in Analytical Engine114

A constant may be been used in conjunction with aggregation in a query.FIG. 5Ashows an example of a database table500for a query illustrating the use of a constant according to one embodiment. Analytical engine114calculates a formula of MAX(K1+K2) over C, where MAX is a maximum function, K1and K2are key figures, and C is the calendar month. The formula is an exception aggregated formula as the results of the formula K1+K2are used to determine the calculation for the MAX formula.

The MAX formula requires that the input data is aggregated up to the granularity level that the formula calculation requires. Then, the results of the formula calculation are again aggregated over the exception aggregation reference characteristics of the formula. In this case, the formula exception aggregation is taking the maximum over the calendar month for the formula result of K1+K2. The calculation part of the formula exception aggregation can be modeled formally as follows:Let M be a set of characteristic values, and let N and F be subsets of M, that is, N,F⊂M.Let r: N→V and g: F→W represent keyfigures.Let: (V ∪ {NULL})×(W ∪ {NULL})→D be a binary function, in the example it is + with its specific NULL handling.The mappingcan be lifted to
N,F: VN×WF->DN∪F
where for l ϵ F ∪ N we define

N,F⁢(r,g)⁢(l):={r⁡(l)g⁡(l)⁢⁢if⁢⁢l∈F⋂Nr⁡(l)NULL⁢⁢if⁢⁢l∈N⁢\⁢FNULLg⁡(l)⁢⁢if⁢⁢l∈F⁢\⁢NThe keyfigure K1has components for January, February, March and April and can be modeled as mapping r where N={c1, c2, c3, c4} and V={15 USD, 50 USD, 20 USD,10USD} and r(c1)=15 USD etc. . . . , whereas the restricted keyfigure K2has only components for January and can be modeled as mapping g where F={c1} and W={15 USD} and (obviously) g(c1)=15USD.When vectors with differing component structures are combined with an exception aggregated formula, the missing components are completed with NULL.

FIG. 5Bshows the calculation of the inner formula of K1+K2according to one embodiment. At503, a column for restricted keyfigure K2over the calendar month is shown. In this column, the value for the month of January is only provided when the restriction is over the month of January. Thus, at504, the value of 15 USD is provided. However, at506-1,506-2, and506-3, respectively, the value of “NULL” is included due to the restriction not applying to the calendar month. NULL means that the value does not exist for that cell. The value of NULL may be different from the value of 0.

At508, the formula is calculated component-wise. As shown, key figure K1is added with key figure K2to determine formula results in the column shown at508.

Analytical engine114then aggregates the results according to the aggregation function over the reference characteristic of calendar month. That is, the maximum of the result for each calendar month is calculated as follows:
MAX(30 USD, 50 USD, 20 USD, 10 USD)=50 USD
In this case, the maximum of the formula results calculated for K1+K2is taken. As can be seen, analytical engine114determines that 50 USD is the maximum of these formula results.

The above example did not use constants; however, constants may be used in exception aggregated formulas. Also, although constants are described with respect to exception aggregated formulas, the constants may be used in other aggregations.

Constants in Exception Aggregated Formulas

If a formula contains constants, analytical engine114may treat the behavior of these constants in two different ways. For example, the constant may have its own data representation or may not have its own data representation.

When a constant has its own data representation, the constant behaves like a key figure. In this case, the constant behaves as if it would have been booked inside a multi-dimensional data model and would have the constant value and the granularity the formula is defined on. To illustrate this, the exception aggregated formula of SUM(K2+100 USD) over C is used.FIG. 6Ashows a database table including data summarizing the formula of SUM(K2+100 USD) according to one embodiment. At602, the characteristic C of calendar month is provided for the months of January 2013, February 2013, March 2013, and April 2013. At604, the values for the keyfigure K2are provided. The key figure in K2may be restricted to the amount in January as described above with respect toFIG. 5B. In this case, January has a value of 15 USD and February, March, and April have the value of NULL. At606, a constant of 100 USD is provided. Reviewing the formula above, the result of K2+100 USD is shown in a column at608. As can be seen, the values in the columns shown at604and606are added together. Even though the months February, March, and April include a NULL value for keyfigure K2, the addition of the constant 100 USD still affects the result of the addition.

After calculating the result of the formula K2+100 USD, analytical engine114performs the exception aggregation to determine the sum of the formula results as follows:
SUM(115 USD+100 USD+100 USD+100 USD)=415 USD

The constant behaves as if it had been booked inside the multi-dimensional data model with a value of 100 for every distinct calendar month. In this case, the constant is a vectorial constant. That is, a value of 100 needs to be represented in the data model for each month of January, February, March, and April. The vectorial constant may be an expensive constant to process by analytical engine114because the constant needs its own data representation in data for the query (e.g., the preliminary database result set) fetched by analytical engine114. That is, analytical engine114needs to monitor the existence of the constant value independently from other parts of the formula.

A constant may also not have its own data representation. In this case, the constant behaves as a scalar value. The data representation for the scalar value is triggered by other formula operands. For example, using the formula SUM(K2*100) over C, the constant of “100” may be a scalar value. In this case, the formula is only calculated whenever a value exists for K2. This is because when K2is NULL, then the value of the constant does not matter as the result of a multiplication with a NULL value will always be NULL.FIG. 6Bshows a table650including the result of the calculation of the formula K2*100according to one embodiment. Only the value for January 2013 is calculated and a result shown at652. Then, analytical engine114performs the exception aggregated formula SUM(K2*100) is SUM(1500 USD)=1500 USD.

The constant inFIG. 6Bdoes not need a data representation because its existence is dependent upon the existence of the keyfigure K2. In this case, analytical engine114does not have to represent the constant as a vector value. Rather, the constant is represented as a scalar value and only used when analytical engine114determines that keyfigure K2exists. Using the constant as a scalar value is cheaper to process because values for each component of the drill down do need to be stored.

Implicit Behavior Rules

As mentioned above, metadata107may model implicit behavior rules that analytical engine114uses to evaluate constants in formulas. In one example, analytical engine114evaluates the formula to determine if the constant should be modeled as a vectorial representation. If none of the implicit behavior rules indicate the constant should be modeled as a vectorial representation, then analytical engine114models the constant as a scalar representation. The following implicit behavior rules may be used, but others may be contemplated:1. A constant behaves like a vector if the constant has no key figure context. This means that the constant is not connected to a key figure within the formula or only connected via operators +, −, AND, OR, XOR, and two-digit Boolean operators. This constant may be referred to as an “unconnected constant.” That is, the constant is not dependent upon the value of the key figure within the formula.2. A constant behaves like a vector if the constant contains a filter explicitly set for the constant and this filter does not completely include the filter of the connected key figure context. For example, the filter may remove a group-by value for a reference characteristic for the constant. In one example, the following formula may be evaluated:
SUM((K1 in Jan, Feb)*(100 in Jan)) overC,
where K1is a key figure with the restriction of the reference characteristics in January and February and 100 is a constant with a restriction in January, and the results of the formula are summed over the calendar month C. In the above formula, the constant 100 only exists in January. Thus, analytical engine114must model the constant as having its own data representation so that it can monitor when the constant exists. That is, analytical engine114models the value of 100 in January and adds the values of NULL for the other calendar months. In this case, the vectorial representation needs to be used.3. In all other cases, the constant becomes a scalar representation. That is, filtered constants are scalar representations. That means in all other cases there is a key figure part in the formula that defines the group by values for which the formula needs to be calculated, and the constant exists for all of the group by values defined by that key figure part, and the formula operator returns NULL when the key figure part of the formula is NULL. In these cases the constant cannot have a “standalone” effect on the result of the formula.
The above rules can be derived from the math representation of the operation. The scalar representation can be used as an optimization for the vectorial representation, if the following 2 conditions apply. This assumes that the constant is the 2ndoperand ofN,F:(1) N⊂F. This implies that the constant has the same value for all components of the keyfigure part.(2)defines its NULL handling such that(NULL, X)=NULL, that is, if the keyfigure operand is NULL, the formula result is NULL, and the constant needs no own data representation.
If the constant is the 1st operand, the dual of the above conditions can be derived as follows:(1) F⊂N. Again, this implies that the constant has the same value for all components of the keyfigure part.(2)defines its NULL handling such that(X, NULL)=NULL, that is, if the keyfigure operand is NULL, the formula result is NULL, and the constant needs no own data representation.
In the above, if the constant is a 2ndoperand of a formula and the key figure operand that is the 1stoperand is NULL, the formula result will be NULL. Because the result is NULL, the constant does not need its own data representation. Therefore, the dual condition also is true.

Explicit Behavior Rules

As mentioned above, constant behavior may be explicitly controlled by using the operators of SCAL( ) and VECT( ) that are associated with or applied directly to a constant within a formula. When used in a formula, the operator explicitly controls the behavior of the constant.

The use of the scalar operator causes analytical engine114to represent the constant as a scalar value when calculating a result of the formula. This provides better performance as the scalar value uses less resources than if the constant was represented as a vector value. That is, a vectorial constant creates a large performance impact by increasing the filter. Also, when not explicitly controlled, a constant used in a formula together with another operand that has constant selection set for its filter, the result received may not be the result the user expected. Constant selection defines a separate filter context, where either the complete outside filter or parts of the outside filter are ignored. A filtered constant that is connected to a key figure with constant selection might not lead to the expected result in all cases. In this case, it may be beneficial for a user to use the scalar operator such that the user can explicitly control the behavior the user intends. An example illustrating this behavior is shown at710below.

FIG. 7Ashows a table700of an example query result according to one embodiment. The table shows results for different queries that may or may not use the SCAL( ) operator. At702, the result for the keyfigure K3is shown as 10, 20, 30, and 40 in the months of January, February, March, and April, respectively. The formula of SUM(keyfigure K3) over calendar month provides the result of 100. In this case, the results of keyfigure K3are summed.

At704, the formula of K3in Jan with CS results in a value of 10 for the months of January, February, March, and April. The constant selection of January ignores the context for each month and chooses the filter for January. Thus, the value for January is used. This is because the key figure K3is restricted with constant selection in January. That is, the result is the same for January, February, March, and April due to the constant selection of the key figure K3in January. Further, for the total, the value is K3in January, which is 10.

At706, the formula SUM(K3in January with CS*3) over C results in the value of 30 for all months. Analytical engine114calculates the value of 30 because of the following rules: According to the implicit rules 3 is a scalar constant. Due to constant selection on the keyfigure K3with the January filter for each month the result of K3in Jan with CS is always 10. The group by values of characteristic C for the formula are defined by K3in Jan with CS, and the only existing values is January in all cases. Therefore for all cells of row706the same calculation 10*3 takes place, which results in 30.

At708, the formula SUM(K3in Jan with CS*3 in Feb) over C is evaluated as NULL for each month. In this case, K3in January is constantly selected and also the constant 3 is restricted to the month of February. K3only has a value for January and the constant 3 only has a value for February and thus all values are NULL.

The value of K3in Jan with CS is the same as described in706. But this time 3 in Feb is a vectorial constant according to the implicit rules, as it contains a filter that does not completely include the filter of the other formula operands. In this case, the values are NULL because the constant 3 is restricted only in the month of February. However, the keyfigure K3is only valid in January. Thus, for the calculation for the month of January, the value for January is 10 and the value for the constant is NULL resulting in a value of NULL.FIG. 7Bshows the results for this formula. At750, the result for K3in January with CS is 10. However, at752, the result of the constant with a restriction for February is NULL because the month of January is being considered. This results in a NULL value shown at754. For the month of February, at756, the value is NULL for K3in Jan with CS. This is because the month of February is being used. At758, the constant value of 3 is used because this calculation meets the requirements of the reference characteristic of February. However, at760, the result is NULL as NULL multiplied by 3 is NULL.

Referring back toFIG. 7A, at710, the formula SUM(K3in Jan with CS*3 in Jan) over C results in the value of 30, NULL, NULL, NULL for the months of January, February, March, and April, respectively. The value for the constant 3 in January is 3, but NULL for other months. According to the implicit rules the constant 3 in January is a vectorial constant, because its filter does not completely include the filter of the other operands. A non-constant selection context can never include the filter of a constant selection context. This results in a value of NULL for February, March, and April. The keyfigure K3in January with CS is calculated again in the same way as in706. The result of 30 for January is received because the constant is restricted to a reference characteristic of January and thus for the January month the formula is calculated as 10*3=30. For the rest of the months, the value of K3is NULL and the value for the constant is NULL meaning the value is NULL as shown inFIG. 7C.

At712, the formula SUM(K3in Jan with CS*3 in Jan CS) over C results in the value of 30 for each month. The constant selection of the constant 3 in Jan means that the reference characteristic in January is ignored for the constant and thus the value of 3 is used for all months. Thus, the constant selection of 3 in January removes the implicit filter from the column context and fixes the calendar month filter to 3. Moreover, according to implicit rules, in this case the constant becomes a scalar constant, because its filter completely includes the filter of the connected keyfigure K3in Jan with CS. This results in the calculation of 10*3 for all months. Constant selection primarily influences the filter, not the order of aggregation. Key figures are implicitly aggregated according to the aggregation defined with the key figure. The constant selection of key figure K3in Jan with CS looks the same for January, February, March, and April. However, when the constant selection is over a reference characteristic found in an outer formula, then the key figure is not aggregated over the calendar month when calculating the formula.

At714, the scalar operator is used in the formula SUM(K3in Jan with CS*SCAL(3 in Jan)) over C. In this case, the constant 3 is a scalar value and only used when the keyfigure K3exists. Because K3in Jan is selected with constant selection, the value of 10 is used for all months. Without using the SCAL( ) operator, analytical engine114would represent the constant 3 as a vector. Basically because of the SCAL( ) operator714behaves exactly the same as712. Because of constant selection the calculation table for Feb, March and April is shown inFIG. 7D.

At716, the scalar operator is used again in the formula SUM(K3in Jan with CS*SCAL(3 in Feb)) over C. The calculation again results in the value of 30 for all months. The same result occurs because the constant 3 is used as a scalar value. With the constant selection of key figure K3in Jan being used, the scalar value of 3 is used to calculate the formula for all months in which the value exists. Without using the SCAL( ) operator, analytical engine114would represent the constant 3 as a vector because the exception aggregation for the constant 3 is over Feb. and the exception aggregation for the key figure K3is over Jan. This means the constant contains a filter explicitly set for the constant and this filter does not completely include the filter of the connected key figure context. For example, the filter for key figure K3may remove a group-by value for a reference characteristic for the constant.

Particular embodiments provide many advantages. One advantage is performance gain. For the following formula “SUM(K1in Jan*3) over calendar month”, without the use of the vectorial representation an intermediate result is needed, that contains one tuple (Jan, K1), and as many tuples of (month, 3) as there are booked months in the data. Therefore, the data would need to be read without any filter just to determine these tuples, but at the very end only the data of January was needed. When this optimization takes place, such as in a high cardinality dimension like customer or product, the effect on the runtime is a factor of 10000 or more.

FIG. 8illustrates hardware of a special purpose computing machine configured with analytical engine114according to one embodiment. An example computer system810is illustrated inFIG. 8. Computer system810includes a bus805or other communication mechanism for communicating information, and a processor801coupled with bus805for processing information. Computer system810also includes a memory802coupled to bus805for storing information and instructions to be executed by processor801, including information and instructions for performing the techniques described above, for example. This memory may also be used for storing variables or other intermediate information during execution of instructions to be executed by processor801. Possible implementations of this memory may be, but are not limited to, random access memory (RAM), read only memory (ROM), or both. A storage device803is also provided for storing information and instructions. Common forms of storage devices include, for example, a hard drive, a magnetic disk, an optical disk, a CD-ROM, a DVD, a flash memory, a USB memory card, or any other medium from which a computer can read. Storage device803may include source code, binary code, or software files for performing the techniques above, for example. Storage device and memory are both examples of computer readable storage mediums.

Computer system810may be coupled via bus805to a display812, such as a cathode ray tube (CRT) or liquid crystal display (LCD), for displaying information to a computer user. An input device811such as a keyboard and/or mouse is coupled to bus805for communicating information and command selections from the user to processor801. The combination of these components allows the user to communicate with the system. In some systems, bus805may be divided into multiple specialized buses.

Computer system810also includes a network interface804coupled with bus805. Network interface804may provide two-way data communication between computer system810and the local network820. The network interface804may be a digital subscriber line (DSL) or a modem to provide data communication connection over a telephone line, for example. Another example of the network interface is a local area network (LAN) card to provide a data communication connection to a compatible LAN. Wireless links are another example. In any such implementation, network interface804sends and receives electrical, electromagnetic, or optical signals that carry digital data streams representing various types of information.

Computer system810can send and receive information through the network interface804across a local network820, an Intranet, or the Internet830. In the Internet example, software components or services may reside on multiple different computer systems810or servers831-835across the network. The processes described above may be implemented on one or more servers, for example. A server831may transmit actions or messages from one component, through Internet830, local network820, and network interface804to a component on computer system810. The software components and processes described above may be implemented on any computer system and send and/or receive information across a network, for example.

Particular embodiments may be implemented in a non-transitory computer-readable storage medium for use by or in connection with the instruction execution system, apparatus, system, or machine. The computer-readable storage medium contains instructions for controlling a computer system to perform a method described by particular embodiments. The computer system may include one or more computing devices. The instructions, when executed by one or more computer processors, may be operable to perform that which is described in particular embodiments.