DE102006008740A1 - Data consistency securing method, involves carrying out modeling of dependencies between data, and producing data structure containing validation counter and/or transaction time stamp and dependence instruction adjacent to basic values - Google Patents

Abstract

The method involves carrying out modeling of dependencies between data (A). A data structure is produced, where the data structure contains a validation counter (G) and/or a transaction time stamp (T) and a dependence instruction (R) adjacent to respective virtual data e.g. basic values. The validation is determined either by values at a time point of change of basic data (B1, B2) by entry in dependent data structures or by comparison of the time stamp in the individual data. The stamp is assigned for a portion at consistent data variations, by which the consistency of the data is verified.

Description

The The invention relates to a method for securing data consistency of interdependent data, which explicitly models dependencies between data, to inconsistencies in dependent Data after changes to recognize their basic data or to immediately restore consistency.

The Problem of dependent Data is currently being solved, by requiring that the entire system has all the data and its dependencies are known and have direct access to all data. In the case of change The base data will then be all dependent data by this global System updated. The dependency descriptions and amendments So they are managed globally.

In Database systems are defined, for example, so-called triggers, who make this update in case of modification of basic data. For each Type or each instance of a base date becomes central the necessary update functionality Are defined. This, however, sets the knowledge of all data and their dependencies ahead.

If Now a date changes, have to all data derived from it will also be changed to data consistency within this record.

A additional Problem arises, if several systems on a common Access data but extend it system-specifically can. In this case, be proprietary Data, i. Data that only one system can interpret, with data blended, which are known to all systems. It is also here possible, that dependencies between the proprietary and the common data, which also applies to changes can lead to inconsistencies in the basic data.

The The object underlying the invention is now, a Method for securing the data consistency of interdependent data specify, in which the above-mentioned disadvantages are avoided.

These Task is achieved by the features of claim 1 solved according to the invention.

The further claims relate to advantageous embodiments of the method according to the invention.

The The invention consists essentially in that, in contrast to usual Method for securing data consistency Dependencies and optional derivation rules decentralized stored in the data, which no parent Collection and management system is necessary and processing of data allows which are not known to all systems involved. The latter means the derived data can can be added to the dataset as required by individual systems without the other systems involved or a complete system must interpret this data. This is made possible by that the data is almost for yourself their update are responsible. The inclusion of a Transaction time stamp also allows precise control over the to be calculated and avoids redundant evaluations. With Help of the above-described methods is evident at all times whether data values are valid or invalid are. Due to the optional description of the derivation regulations, the Data values are recalculated.

in the The invention is based on preferred embodiments explained in more detail. there shows

1 a representation for explaining a first embodiment in which dependencies are stored starting from the basic data,

2 a representation for explaining a second embodiment in which dependencies are stored based on the derived data and

3 a representation for explaining a third embodiment in which dependencies are stored both based on basic data and on the basis of the derived data.

The prerequisite for inconsistencies in dependent data after changes to their basic data recognizing or immediately restoring consistency is an explicit modeling of the dependencies between data. In contrast to the previous solution, no superordinate overall system is necessary to manage these dependencies, but these dependencies are stored directly in the affected data. The validity of values is determined either at the time of changing base data via a note in the dependent data structures or by comparing transaction time stamps in the individual data. In contrast to a normal time stamp, a transaction time stamp is assigned in each case for a set of consistent data changes, ie, all data with an identical transaction time stamp is guaranteed to be consistent with each other and underlying data, that is, data on which the considered data is dependent, with an older transaction time stamp. If there is a dependency between two dates and the date of the underlying data is younger than the derived date, then the consistency of the derived date must be checked.

If Not only can the consistency of data be checked, beyond that optionally also the derivation rule is deposited, which describes how the derived data is calculated from the base data. This allows an automatic calculation of the derived data.

• 1. eine Gültigkeitsmarkierung und/oder einen Transaktionszeitstempel
• 2. Abhängigkeitsbeschreibungen
• 3. optional Ableitungsvorschriften

The invention is based on a data structure which, in addition to the actual data, has the following components:

• 1. a validity mark and / or a transaction time stamp
• 2. dependency descriptions
• 3. optional derivation rules

If Calculation rules only starting from the basic data to the derived data, only basic data can be changed. This must be ensured by labeling or access mechanisms become. The direct modification of derived data is then allowed if the calculation rules are stored bidirectionally are, i. Also known is how a base date derived from the Date results. This then results in additional conditions to the Procedures that will not be considered separately below.

ever according to the requirements in the system can be one of the following three methods are applied. An example is used which from a weight indication and a size specification the body mass index (BMI), from which then a classification into a weight classification he follows. The BMI is calculated from the weight divided into kilograms by the size in meters to square. The weight classification refers to the BMI and determines over a table classification in underweight, normal weight, overweight, etc.

To the embodiments shown below are respectively for a better understanding of implementation examples specified in XML. These examples are deliberately kept very simple or There are far more complex applications, for example in terms of Type of referencing, storage of timestamp or presentation the calculation rules.

Embodiment 1

The dependencies are stored here starting from the basic data.

In this case will be changed on the basic data via the dependencies all derived data identified - it must also be recursively derived Data dependent on the base date Data to be identified. To determine the inconsistency in case of a change a base date all dependent Data about it informed that they are invalid Values are based. This can e.g. by putting a simple one Boolean "switch", the component the data is. If derived data is accessed, so is it their validity ascertainable. This ensures that each value in the system is valid is known.

This Procedure can be used if only the validity must be determined by values. An update of the derived Data can then be system dependent respectively.

In 1 this procedure is shown step by step. Step 1 represents the initial situation in which the dependencies are formulated from the basic data B1 and B2 to the derived data A. When a base value W2 changes, the dependent values WA must be marked as invalid, for example, with the aid of a validation switch G, as can be seen in steps 2a and 2b.

Simple implementation example in XML

There are two applications that work on a common record. The applications should be able to determine if the data is up-to-date during shared access. The first application creates the following data record:

The second application now changes the base attribute Weight and applies the procedure described in 1. This will change the data as follows:

The first application checks After the procedure before each read whether the data is still valid. When trying to read the weight classification attribute the first application determines that this value is no longer valid and must trigger a recalculation.

Embodiment 2

The dependencies R and possibly a derivation rule V are stored in the derived data. In addition, each date must also include a time stamp or a transaction time stamp T, as in step 1 of FIG 2 is shown. If changes are now made to the basic data B1 or B2, this change, as can be seen from step 2, is not propagated to derived data. In this method, the base data need no knowledge of dependent data. In addition, the transaction time stamp T of the base date is updated. The values of the derived data are not consistent with their base data at this time because their change has not yet been adopted. The amount of data is temporarily in an inconsistent state. Assuming that consistent data is always expected when reading the data, an adjustment must be made at the latest when accessing the derived data. In this case, based on dependency descriptions a or b of the derived date, all base data is determined, which may extend recursively over several levels. If only the validity of the current value is to be checked, an analysis of the transaction time stamps T of the basic data is sufficient. If their transaction timestamps are older or the same age as the transaction timestamps of the derived date A, their value is valid and can be used directly if necessary.

If not only the validity is to be checked, then the derivative value V must be used to determine the current value of the derived date. In addition, the current transaction timestamp must be set. This transaction timestamp may also correspond to the transaction timestamp of the most recent change to the base data. Thus, the current value of the date is known and documented to which level of the basic data the calculated value is consistent. This is in 2 to see in step 3.

This Procedure may be useful for large Data sets with rather few accesses to the derived data be applied. The depth of dependencies between the data or their networking should be rather low in order to be efficient To ensure updating.

easy Implementation example in XML

There are again two applications that work on a common database. Application 1 generates the following data record:

Application 2 now changes the base attribute Weight and sets the transaction time stamp accordingly:

Application 1 now wants to read the value of the weight classification attribute and now has to check the validity. It tracks the dependencies via the attribute BMI up to the basic attributes size and weight. For the base attribute Weight Application 1 determines that the time stamp is newer than the weight attribute to be read and must now trigger a recalculation. First, the attribute BMI is recalculated from bottom to top according to the rule stored there, and then according to its rule the attribute weight classification. Application 1 then saves the newly calculated data as follows:

Embodiment 3

This procedure is a combination of the two previous methods. The Ab Dependencies are stored here on the basis of the basic data and the derived data. In addition, the derivation rules are also stored in the derived data.

In 3 In step 1, double dependency modeling is apparent. When the basic data is changed, the changes are propagated to the derived data, as in the first method, where they are merely noted that the current value is not consistent with the base values, which is shown in FIG 3 in step 2 can be seen. When accessing the derived data, their validity is then checked on the basis of this memorandum and then proceeded according to the second method. If the value is valid, it can be used immediately, otherwise the base data is determined using the dependency descriptions and the current value is calculated from this base data. The validity notes are then reset. The result of this process is in the 3 to see in step 3 by way of example.

This Procedure is useful for large Data sets with numerous accesses to the derived data. The depth of dependencies is not relevant here.

A Variant of this embodiment is that the data is not marked as invalid, but be recalculated, which keeps the data up-to-date and consistent.

easy Implementation example in XML

As with the previous examples, two applications work on a common database, and application 1 generates the following data record:

Application 2 changes the value of the Weight attribute and additionally identifies the tree that has become invalid:

Application 1 now wants to read the value of the attribute BMI and first checks the validity of the value by means of the Valid property of the attribute. Since the BMI attribute is invalid, it must be recalculated starting from the base values using the calculation rule stored in the Formula property. Application 1 writes back the new date and updates the record as follows:

Claims (5)

Method for securing the data consistency of interdependent Data in which a modeling of dependencies between data thereby is done that a data structure is generated, in addition to the respective actual data (WA, W2), a validity mark (G) and / or a transaction time stamp (T) and at least one dependency description Contains (R). The method of claim 1, wherein the validity of values either at the time of changing base data over one Note in the dependent Data structures or over a comparison of transaction timestamps in the individual data is determined, wherein a transaction time stamp each for a quantity on consistent data changes is awarded, where the consistency of the data is checked, if a dependency between at least two dates and a base date is younger as a derived date. The method of claim 1, wherein in the data structure additionally at least one derivation rule is included. Method according to claim 3, at least a derivation rule (V) describes how the derived data (A) are calculated from the basic data (B1, B2) and in which an automatic calculation of the derived data with the help of Derivation rule takes place. Method according to one of the preceding claims, in This is ensured by labeling or access mechanisms is that only basic data changeable are, provided only calculation instructions from the basic data to the derived ones Data are formulated and a direct modification of derived Data is only allowed if in the calculation rules It defines how a base date is derived from the derived date results.