Patent Grant
11991272
Embodiments generally relate to data encryption in a database management system, and more particularly to handling tenant-specific encryption for pre-existing containers in connection with databases that employ group-level encryption to support multi-tenant data privacy.
Encryption of persisted in-memory database data is typically done at the level of a persisted data volume. Such data-volume-level encryption has the benefit of protecting the persisted data should physical access be improperly obtained to media containing the persisted database data. However, in the case of cloud-based, multi-tenant applications using an in-memory database, the data of multiple customers may be stored in a single in-memory database system. In such a case, the data for each customer in the multi-tenant application should be separately encrypted such that each individual customer has exclusive control over the customer's own encryption key(s), thereby ensuring group-level data privacy for the customer of a multi-tenant cloud-based application. Moreover, such group-level encryption and decryption processes should not require re-implementation of multi-tenant, cloud-based applications. Difficulties arise in multi-tenant, cloud-based applications when assigning encryption groups to pre-existing containers.
Accordingly, what is needed is a method for efficiently and reliably enabling tenant-specific encryption of containers using group-level encryption in an in-memory database with persistency, without requiring application redesign, thereby addressing the above-mentioned problems.
Disclosed embodiments address the above-mentioned problems by providing one or more non-transitory computer-readable media storing computer-executable instructions that, when executed by a processor, perform a method for tenant-specific encryption of containers in connection with a database employing group-level encryption, the method comprising receiving an assignment of an encryption group identifier to containers, the encryption group identifier defining an encryption key for encrypting the containers, responsive to receiving the assignment, creating a special container entry corresponding to the containers, receiving a commit operation of the assignment of the encryption group identifier, initializing a job for encrypting the container according to the encryption group identifier, initiating a flush operation by which the container is re-encrypted using the encryption key and persisted to a data volume, and deleting the special container entry upon completion of the flush operation. The special container entry may comprise a processing state. The special container entry may be initialized in an inactive state.
This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter. Other aspects and advantages of the present teachings will be apparent from the following detailed description of the embodiments and the accompanying drawing figures.
Embodiments are described in detail below with reference to the attached drawing figures, wherein:
The drawing figures do not limit the present teachings to the specific embodiments disclosed and described herein. The drawings are not necessarily to scale, emphasis instead being placed upon clearly illustrating the principles of the disclosure.
In some cases, cloud-based, multi-tenant applications need to provide data privacy on a tenant-by tenant basis, and in some cases a particular tenant has the requirement to be responsible for the tenant's own encryption keys so that even an operator of a cloud-based application or a data center in which the application is being hosted will not have access to the tenant's data. In some embodiments, to encrypt data on a tenant-by-tenant basis, encryption groups are employed. In some embodiments, each tenant is associated with its own encryption group. In some alternative embodiments, tenants share encryption groups. A data container is a logical unit of persistence which may be encrypted at a group-level. In some embodiments, each data container is assigned to a particular encryption group. Data within one encryption group is encrypted and decrypted with the same group-level encryption key. In some embodiments, metadata associated with each container includes an encryption group identifier corresponding to which encryption group with which the container is associated. In these embodiments, this is the container directory entry. The container may contain data for a SQL table, a column of a SQL table, or a single LOB from a LOB column for a table, for example.
A converter is a data structure that maintains a mapping from logical page numbers to corresponding physical block numbers within one or more data volumes. In some embodiments, converter metadata associated with a converter stores a value corresponding to the encryption group that each data page belongs to within a converter entry in the converter metadata. The converter entry provides a mapping from logical page number to physical block number. In some embodiments, a database operation may require that a data container read in one or more data pages associated with the data container. In these embodiments, the data container provides a source of information regarding an association between an encryption group identifier and a page access function. In some embodiments, the corresponding encryption group identifier is used to decrypt the loaded group-level encrypted page content. The encryption group identifier is also stored within a transient page control block to be used for encrypting page content while flushing a page at such time as the page needs to be persisted after having been modified by a database operation. A transient page control block is an object that stores additional information for the page which is only needed for a limited amount of time. In some embodiments, a transient control page is a control block which is stored within a resource container and which holds a pointer to the actual in-memory representation of the page.
In some embodiments, only data page content is encrypted and/or decrypted with a corresponding group-level encryption key. By contrast, in these embodiments, the page header is not encrypted with the group-level encryption key. In some embodiments, the page header is encrypted with a data volume encryption key. In some alternative embodiments, the page header is unencrypted. The page header is not encrypted with the group-level encryption key so that that the information from the page header can be read for database internal operations such as backup and recovery and data volume resizing, where pages need to be accessed by the database system, but the corresponding user (tenant) content needs to remain encrypted with the group-level encryption key(s).
In some embodiments, pre-existing data to which no encryption group has been assigned is assigned to an encryption group. When an encryption group identifier is assigned, a container entry may be created to log the assignment of the encryption group identifier to the pre-existing data. By logging the assignment and tracking a state thereof, the encryption group identifier may be correctly assigned in the event of a hardware crash or shutdown during assignment. Each container has a container directory entry assigned to it, and a container is made up of a set of pages which store corresponding data associated with the particular container. Associated container directory entries store encryption group identifiers for containers as described above. Additionally, each container directory entry may have a special container entry created therefor to track a state of the assignment. The container entry may store a single state. The single state may be one of an inactive state, a to-be-processed state, or an in-process state and may be initialized in the inactive state. When commitment of the encryption group identifier assignment is received, the state may be changed to the to-be-processed state. A job may then be initialized to re-encrypt the pre-existing data according to the newly assigned encryption group identifier. Upon initiation, each container entry in the to-be-processed state may be changed to an in-progress state. After loading the pre-existing data back to disk and changing the encryption group identifier, the pre-existing data may be flushed back to disk such that the pre-existing data is decrypted according to the encryption group identifier.
The subject matter of the present disclosure is described in detail below to meet statutory requirements; however, the description itself is not intended to limit the scope of claims. Rather, the claimed subject matter might be embodied in other ways to include different steps or combinations of steps similar to the ones described in this document, in conjunction with other present or future technologies. Minor variations from the description below will be understood by one skilled in the art and are intended to be captured within the scope of the present claims. Terms should not be interpreted as implying any particular ordering of various steps described unless the order of individual steps is explicitly described.
The following detailed description of embodiments references the accompanying drawings that illustrate specific embodiments in which the present teachings can be practiced. The described embodiments are intended to illustrate aspects of the disclosed embodiments in sufficient detail to enable those skilled in the art to practice the present teachings. Other embodiments can be utilized, and changes can be made without departing from the claimed scope of the claims. The following detailed description is, therefore, not to be taken in a limiting sense. The scope of embodiments is defined only by the appended claims, along with the full scope of equivalents to which such claims are entitled.
In this description, references to “one embodiment,” “an embodiment,” or “embodiments” mean that the feature or features being referred to are included in at least one embodiment of the technology. Separate reference to “one embodiment” “an embodiment”, or “embodiments” in this description do not necessarily refer to the same embodiment and are also not mutually exclusive unless so stated and/or except as will be readily apparent to those skilled in the art from the description. For example, a feature, structure, or act described in one embodiment may also be included in other embodiments but is not necessarily included. Thus, the technology can include a variety of combinations and/or integrations of the embodiments described herein.
Turning first to
Index server 110 may contain in-memory data stores and engines for processing data. Index server 110 may also be accessed by remote tools (via, for example, SQL queries), that can provide various development environment and administration tools. Additional details regarding an example implementation of index server 110 is described and illustrated in connection with diagram 200 of
In some embodiments, name server 115 is responsible for information about various topologies associated with database system 105. In various exemplary distributed database systems, name server 115 provides descriptions regarding where various components are running and which data is located on which server. In connection with database system 105 having multiple database containers, name server 115 may provide information regarding existing database containers. Name server 115 may also host one or more system databases. For example, name server 115 may manage the information regarding existing tenant databases, which tenant databases are isolated from one another. Unlike name server 115 in a single-container database system, name server 115 in a database system 105 having multiple database containers does not store topology information such as the location of tables in a distributed database. In a multi-container database system 105 such database-level topology information can be stored as part of data catalogs associated with the various isolated tenant databases.
Application server 120 can enable native web applications used by one or more client applications 150 accessing database system 105 via a web protocol such as HTTP. In various embodiments, application server 120 allows developers to write and run various database applications without the need to provide an additional application server. In some embodiments, application server 120 can also be used to run web-based tools 155 for administration, life-cycle management, and application development. Other administration and development tools 160 can directly access index server 110 for, example, via SQL and/or other protocols.
In various embodiments, extended store server 125 can be part of a dynamic tiering option that can include a high-performance disk-based column store for very big data up to the petabyte range and beyond. Less frequently accessed data (for which is it non-optimal to maintain in main memory of the index server 110) can be maintained in connection with extended store server 125. Dynamic tiering associated with extended store server 125 allows for hosting of very large databases with a reduced cost of ownership as compared to conventional arrangements.
In various embodiments, DDI server 130 may be a separate server process that is part of a database deployment infrastructure. This infrastructure may be a layer of database system 105 that simplifies deployment of database objects using declarative design time artifacts. DDI can ensure a consistent deployment, for example by guaranteeing that multiple objects are deployed in the right sequence based on dependencies, and by implementing a transactional all-or-nothing deployment.
In some embodiments, data provisioning server 135 provides enterprise information management and enables capabilities such as data provisioning in real time and batch mode, real-time data transformations, data quality functions, adapters for various types of remote sources, and an adapter software design kit (SDK) for developing additional adapters. In various embodiments, streaming cluster 140 allows for various types of data streams (i.e., data feeds, etc.) to be utilized by database system 105. Streaming cluster 140 allows for both consumption of data streams and for complex event processing.
Turning now to
Once a session is established, client applications 145 typically use SQL statements to communicate with the index server 110 which can be handled by SQL processor 212 within the request processing and execution control component 210. Analytical applications may employ MDX language expressions, which may be evaluated in connection with MDX processor 222. For graph data, applications may employ GEM (Graph Query and Manipulation) via GEM processor 216, a graph query and manipulation language. In various embodiments, SQL statements and MDX queries may be sent over the same connection with the client application 145 using the same or similar network communication protocols. In some embodiments, GEM statements may be sent using a built-in SQL system procedure.
In various embodiments, index server 110 includes an authentication component 204 that can be invoked with a new connection with a client application 145 is established. Users can be authenticated either by the database system 105 itself (login with user and password) or authentication can be delegated to an external authentication provider. In some embodiments, authorization manager 206 can be invoked by other components of database system 105 to check whether a particular user has the required privileges to execute a requested operation. In various embodiments, requested operations in the form of statements or queries may be processed in the context of a transaction having a beginning and end so that any such transaction may be committed or rolled back. New sessions may be implicitly assigned to a new transaction. In various embodiments, index server 110 includes transaction manager 244 that coordinates transactions, controls transactional isolation, and keeps track of running and closed transactions. When a transaction is committed or rolled back, the transaction manager 244 can inform the involved engines about this event so they can execute necessary actions. Transaction manager 244 can provide various types of concurrency control and transaction manager 244 can cooperate with a persistence layer 246 to persist atomic and durable transactions.
In various embodiments, incoming SQL requests from client applications 145 are received by SQL processor 212. In some embodiments, data manipulation statements are executed by SQL processor 212 itself. In these embodiments, other types of requests are delegated to respective components for processing a corresponding type of request. Data definition statements can be dispatched to metadata manager 208, transaction control statements can be forwarded to transaction manager 244, planning commands can be routed to a planning engine 218, and task related commands can be forwarded to a task manager 224 (which can be part of a larger task framework) Incoming MDX requests can be delegated to the MDX processor 222. Procedure calls can be forwarded to the procedure processor 214, which further dispatches various calls, for example to a calculation engine 226, GEM processor 216, repository 230, or DDI proxy 228.
In various embodiments, index server 110 also includes planning engine 218 that enables implementation of planning applications, for instance for financial planning, to execute basic planning operations in the database layer. One such basic operation is to create a new version of a data set as a copy of an existing one while applying filters and transformations. For example, planning data for a new year can be created as a copy of the data from the previous year. Another example for a planning operation is the disaggregation operation that distributes target values from higher to lower aggregation levels based on a distribution function.
In various embodiments, SQL processor 212 includes an enterprise performance management (EPM) runtime component 220 that can form part of a larger platform providing an infrastructure for developing and running enterprise performance management applications in connection with database system 105. While planning engine 218 typically provides basic planning operations, in some embodiments, exemplary EPM platforms provide a foundation for complete planning applications, based on by application-specific planning models managed in connection with database system 105.
In various embodiments, calculation engine 226 provides a common infrastructure that implements various features such as SQL processing, SQLScript interpretation, evaluation of MDX and/or GEM, tasks, and execution of planning operations. In various embodiments SQL processor 212, MDX processor 222, planning engine 218, task manager 224, and GEM processor 216 can translate various corresponding programming languages, query languages, and models into a common representation that is optimized and executed by calculation engine 226. In various embodiments, calculation engine 226 implements those features using temporary results 240 which can be based, in part, on data within the relational stores 232.
Metadata can be accessed via metadata manager 208. Metadata, in this context, can comprise a variety of objects, such as definitions of relational tables, columns, views, indexes and procedures. In some embodiments, metadata of all such types can be stored in one common database catalog for all stores. In these embodiments, the database catalog can be stored in tables in row store 236 forming part of a group of relational stores 232. Other aspects of database system 105 including, for example, support and multi-version concurrency control can also be used for metadata management. In distributed systems, central metadata is shared across servers and metadata manager 208 can coordinate or otherwise manage such sharing.
In various embodiments, relational stores 232 provide a foundation for different data management components of index server 110. In these embodiments, relational stores can, for example, store data in main memory. In these embodiments, row store 236, column store 238, and federation component 234 are all relational data stores which can provide access to data organized in relational tables. Column store 238 can stores relational tables column-wise (i.e., in a column-oriented fashion, etc.). Column store 238 can also comprise text search and analysis capabilities, support for spatial data, and operators and storage for graph-structured data. With regard to graph-structured data, from an application viewpoint, column store 238 could be viewed as a non-relational and schema-flexible, in-memory data store for graph-structured data. However, in various embodiments, such a graph store is not technically implemented as a separate physical data store. Instead, the graph store is built using column store 238, which may be provided in connection with a dedicated graph API.
In various embodiments, row store 236 stores relational tables row-wise. When a table is created, a creator specifies whether the table is to be row- or column-based. In various embodiments, tables can be migrated between the two storage formats of row- and column-based. While certain SQL extensions may be only available for one kind of table (such as the “merge” command for column tables), standard SQL may be used in connection with both types of tables. In various embodiments, index server 110 also provides functionality to combine both kinds of tables in one statement (join, sub query, union).
Federation component 234 can be viewed as a virtual relational data store. The federation component 234 can provide access to remote data in external data source system(s) 254 through virtual tables, which can be used in SQL queries in a fashion similar to normal tables. Database system 105 can include an integration of non-relational data store 242 into the index server 110. For example, the non-relational data store 242 can have data represented as networks of C++ objects, which can be persisted to disk or other persistent storage. Non-relational data store 242 can be used, for example, for optimization and planning tasks that operate on large networks of data objects, for example in supply chain management. Unlike row store 236 and column store 238, non-relational data store 242 does not use relational tables; rather, objects can be directly stored in containers provided by persistence layer 246. Fixed size entry containers can be used to store objects of one class. Persisted objects can be loaded via their persisted object identifiers, which can also be used to persist references between objects. In addition, access via in-memory indexes is supported. In that case, the objects need to contain search keys. In various embodiments, an in-memory search index is created on first access. Non-relational data store 242 can be integrated with the transaction manager 244 to extends transaction management with sub-transactions, and to also provide an alternative locking protocol and implementation of multi-version concurrency control.
An extended store is another relational store that can be used or otherwise form part of database system 105. In some embodiments, the extended store can, for example, be a disk-based column store optimized for managing very big tables, which tables are not meant to be kept in memory (as with relational stores 232). In various embodiments, the extended store can run in extended store server 125 separate from index server 110. Index server 110 can use the federation component 234 to send SQL statements to extended store server 125.
Persistence layer 246 is responsible for durability and atomicity of transactions. Persistence layer 246 can ensure that database system 105 is restored to a most recent committed state after a restart and that transactions are either completely executed or completely undone. To achieve this goal in an efficient way, persistence layer 246 can use a combination of write-ahead logs, undo and cleanup logs, shadow paging and save points. Persistence layer 246 can provide interfaces for writing and reading persisted data and it can also contain a logger component that manages a recovery log. Recovery log entries can be written in the persistence layer 246 (in recovery log volumes 252) explicitly by using a log interface or implicitly when using the virtual file abstraction. Recovery log volumes 252 can include redo logs which specify database operations to be replayed whereas data volume 250 contains undo logs which specify database operations to be undone as well as cleanup logs of committed operations which can be executed by a garbage collection process to reorganize the data area (e.g., free up space occupied by deleted data etc.).
Persistence layer 246 stores data in persistent disk storage 248 which, in turn, can include data volumes 250 and/or recovery log volumes 252 that can be organized in pages. Different page sizes can be supported, for example, between 4 KB and 16 MB. In addition, superblocks can also be supported which can have a larger size such as 64 MB and which can encapsulate numerous pages of different sizes. In various embodiments, database data is loaded from disk storage 248 and stored to disk page-wise. For read and write access, pages may be loaded into a page buffer in memory. Such a page buffer need not have a minimum or maximum size, rather, all free memory not used for other things can be used a page-buffer cache. If the memory is needed elsewhere, least recently used pages can be removed from the page-buffer cache. If a modified page is chosen to be removed, the page first needs to be persisted to disk storage 248. While the pages and the page-buffer cache are managed by persistence layer 246, the in-memory stores (i.e., the relational stores 232) can access data directly, within loaded pages.
As noted above, the data volumes 250 can include a data store that together with undo and cleanup log and recovery log volumes 252 comprise the recovery log. Other types of storage arrangements can be utilized depending on the desired configuration. The data store can comprise a snapshot of the corresponding database contents as of the last system save point. Such a snapshot provides a read-only static view of the database as it existed as of the point (i.e., time, etc.) at which the snapshot was created. Uncommitted transactions, at such time, are not reflected in the snapshot and are rolled back (i.e., are undone, etc.). In various embodiments, database snapshots operate at the data-page level such that all pages being modified are copied from the source data volume to the snapshot prior to their being modified via a copy-on-write operation. The snapshot can store such original pages thereby preserving the data records as they existed when the snapshot was created.
System save points (also known in the field of relational database servers as checkpoints) can be periodically or manually generated and provide a point at which the recovery log can be truncated. The save point can, in some variations, include an undo log of transactions which were open in the save point and/or a cleanup log of transactions which were committed in the save point but not yet garbage collected (i.e., data which has been deleted by these transactions has been marked as deleted but has not been deleted in a physical manner to assure multi-version concurrency control).
In some embodiments, a recovery log comprises a log of all changes to database system 105 since the last system save point, such that when a database server is restarted, its latest state is restored by replaying the changes from the recovery log on top of the last system save point. Typically, in a relational database system, the previous recovery log is cleared whenever a system save point occurs, which then starts a new, empty recovery log that will be effective until the next system save point. While the recovery log is processed, a new cleanup log is generated which needs to be processed as soon as the commit is replayed to avoid a growing data area because of deleted but not garbage collected data. In some embodiments, shadow pages that are designated to be freed are freed in connection with such a cleanup log. In some embodiments, a garbage collection process executes periodically to free data pages that are designated to be freed.
As part of a database system recovery/restart, after the save pointed state of data is restored, and before processing of the recovery log commences, all cleanup logs can be iterated through and, in implementations using a history manager, passed to the history manager for asynchronous garbage collection processing. In addition, it can be checked if there are older versions of the cleanup log present in the save point which need to be processed synchronously with regard to the recovery log. In such cases, recovery log processing can wait until garbage collection of old versions of cleanup logs finish. However, recovery log processing can commence when there are newer versions of cleanup logs for garbage collection. In cases in which no old versions of cleanup logs exist, recovery log replay can start immediately after the cleanup log from the save point has been passed to the history manager.
A typical save point can have three phases. First, in the pre-critical phase all modified pages in the relational stores 232 (which are loaded into memory) can be iterated through and flushed to the physical persistence disk storage 248. Second, a critical phase can block all parallel updates to pages in the relational stores 232 and trigger all the remaining I/O (i.e., I/O for pages still being modified when entering the critical phase) for the physical persistence disk storage 248 to ensure the consistent state of data. Lastly, a post-critical phase can wait for all remaining I/O associated with the physical persistence disk storage 248.
In various embodiments, database system 105 can be recovered after a failure or other error using information within the recovery log volumes 252 and the data volumes 250. As part of a recovery operation, pages from the backup storage 248 are streamed into the page-buffer cache in the main memory of database system 105. These pages can have different sizes from 4 KB to 16 MB, etc. For smaller page sizes, the write I/O can be slow (i.e., processing numerous small pages can create a bottleneck for a resource flushing thread, etc.). To overcome this restriction, in some variations, multiple pages can be filled in-memory into a superblock (which is a page of a different, larger size such as 64 MB), then the complete superblock can be written to disk 248.
In order to address the issues with write I/O, pages are copied into a superblock. When the database system 105 utilizes encryption for security purposes, each page is encrypted when the page is put into the superblock by a recovery channel (which is a single thread). Given that this operation is single threaded, the page-by-page encryption can be a bottleneck which can cause database recovery to require hours and/or days to complete.
For normal pages (i.e., non-superblocks, etc.), instead of encrypting such pages in the recovery channel, the pages can be encrypted when being flushed to the disk storage 248. With superblocks, additional information is required to encrypt each page. Within a recovery channel, the small pages are copied into a superblock and a control block (i.e., the superblock control block) is generated for the superblock. The control block can be a transient object that includes for each page such as an encryption key and an initialization vector (i.e., a fixed-size input to a cryptographic primitive that can be random or pseudorandom, etc.). When the superblock is filled with small pages, a resource flush thread, using a plurality of helper threads (e.g., 64 helper threads, etc.), encrypts the pages in the superblock in parallel using the information within the control block and causes the superblock to be flushed to disk storage 248.
Turning now to
Each of the primary system 305a and secondary system 305b may include a load balancing functionality. Such load balancing functionality may for example be contained within a distinct load balancing server 370a or 370b. But such load balancing functionality may be managed by any suitable processing system. For example, application server 120 of
As depicted in
Load balancing of resources between primary system 305a and secondary system 305b may give rise to several complicating issues. For example, if either of requests 355, 365 requires writing to one or more data tables, or modifying a data table, then the two systems 305a, 305b may diverge. After many instances of write requests being distributed between primary system 305a and secondary system 305b, the two systems would be substantially inconsistent, and likely unsuitable as replacements for each other. In another example, an application request, e.g., 365, may perform a write transaction that is followed by a read transaction, e.g., 355, related to the data written by the write request 365. If the write request is allocated to the primary system 305a, the read request would obtain a different result depending on whether the subsequent read transaction is carried out by the primary system 305a or by the secondary system 305b.
Load balancing in a combination high availability disaster recovery system, by distributing a portion of the workload of a primary data system to a hot-standby or backup system should be carried out in a manner that would not disturb the principal purpose of the backup system, which is to substantially eliminate downtime in a high availability system by enabling quick and efficient recovery of operations. In other words, as a rule load balancing cannot break the hot-standby. Given this principal purpose, any solution that enables load balancing of workload between a primary system and a backup system should maintain the backup system in an identical, or nearly identical, state as the primary system. Such a solution should also avoid or prohibit any actions which may cause the state of the backup system to substantially diverge from the state of the primary system. In this way, in the event of a partial or total failure of the primary system due to disaster, the backup system can failover to a primary system mode with minimal or no impact to client applications. In some embodiments, snapshots may be employed to facilitate database system replication.
Turning now to
At step 402, assignment of an encryption group identifier to a container storing pre-existing data may be received. In some embodiments, the pre-existing data comprises a table. The table may store various data pages. For example, data from one SQL table may be stored in one or more containers, wherein each of the one or more containers has exactly one container directory entry comprising at least one data page. The table may be assigned to a schema which itself may be assigned to the tenant. In some embodiments, pre-existing schema/tables are assigned to new tenants, wherein the tenants have an associated encryption group identifier. As such, the schema/tables that are now hierarchically below the tenant may be assigned the encryption group identifier associated with the tenant. Each container may have a container directory entry created therefor. The container directory entry may store the encryption group identifier for the corresponding container, a corresponding multi-version concurrency control (MVCC) commit timestamp, and associated metadata. For containers without an encryption group identifier, the MVCC time stamp may be set to “invalid,” and the encryption group identifier set to “unassigned.” The encryption group identifier and the MVCC timestamp may define how the corresponding container should be encrypted. In some embodiments, the associated metadata comprises a container type, a first page number, a root page number, or any combination thereof. In some embodiments, the first page number is used when the container is organized as a linked list of pages. In some embodiments, the root page number is used when the container is organized as a B-tree. A container directory may comprise the container directory entries.
At step 404, a validity check may be performed. The validity check may comprise determining if the assignment of the encryption group identifier is a valid assignment. A valid assignment may comprise an assignment of the encryption group identifier to a container having an “unassigned” encryption group identifier, and an “invalid” MCCV timestamp. If the assignment is valid processing may proceed to step 408. If the assignment is not valid, processing may proceed to step 406 whereby an error is thrown and processing may end.
At step 408, a special container entry may be created corresponding to the container directory entry, a redo log may be created, and the container directory entry may be modified. In some embodiments, modifying the container directory entry comprises changing the encryption group identifier thereof and setting the MVCC timestamp to indicate that the transaction is currently uncommitted. The special container entry may describe the type of re-encryption operation to perform. In some embodiments, the special container entry has one of an inactive state, a to-be-processed state, or an in-process state, as discussed further below with respect to
In some embodiments, re-encryption is logged in a log entry, wherein the log entry comprises the entry identifier identifying the special container entry. The UNDO/CLEANUP log may be used to handle commit or rollback of the transaction as discussed below. If any new pages are created for the container having the newly-assigned encryption group identifier, these pages may be assigned the old encryption group identifier of “unassigned” because it is unknown whether the newly-assigned encryption group identifier will be committed. The decision for new pages to take the old encryption group identifier or the new encryption group identifier is based on the MVCC timestamp. Because there is a single encryption group identifier and a single MVCC timestamp, the MVCC timestamp may only be changed from unassigned to one of the other states.
At step 410, commitment or rollback of the transaction assigning the encryption group identifier to the container may be received. If a rollback is received, processing may proceed to step 412. If a commit is received, processing may proceed to step 414. In some embodiments, database operations described herein are executed using data definition language (DDL). As such, a DDL statement may include a commit functionality or a rollback functionality. At step 412, whereby the assignment is rolled back, the undo log may be processed. Processing of the undo log may comprise resetting the encryption group identifier in the container directory entry to “unassigned” and resetting the MVCC timestamp to “always visible.” Further, the special container entry corresponding to the container directory entry may be deleted.
At step 414, whereby commitment of the encryption group identifier was received, the cleanup log may be processed. In some embodiments, processing the cleanup log comprises changing the status of the special container entry from the inactive state to the to-be-processed state. Further, a valid savepoint version may be set to the current savepoint version.
At step 454, a job may be initiated to re-encrypt the data pages. Once the job is initiated, the special container entries having to-be-processed states may have their states changed to an in-process state. In some embodiments, the job comprises iterating over all pages in the container corresponding to the special container entry and loading the pages from disk. Thereafter, a check may be performed to determine if the assigned encryption group identifier for each page is equivalent to the new encryption group identifier for the container. If the two identifiers are unequal, the encryption group identifier for the page may be changed to match that of the container, and a flush to disk may be triggered to re-encrypt the page. Otherwise, no change to the page may be made.
A scanner may periodically scan all special container entries to determine whether any container entries are in the to-be-processing state and initiates the job if a container entry with a to-be-processed state is found. In some embodiments, the scanner performs a scan when a new savepoint version of the database is created. In some embodiments, a user can define a schedule for scanning container entries. In some embodiments, a counter is employed to track the number of container entries in the to-be-processed state. If the counter is zero, the scanner may not perform a scan. In some embodiments, the counter is transient and stores data only in memory. Alternatively, or additionally, jobs may be manually initiated by a user via a user interface, a SQL statement, or the like. After the special container entries have been processed, at step 456, the container entry may be deleted and removed from the container.
Turning now to
Computer-readable media include both volatile and nonvolatile media, removable and nonremovable media, and contemplate media readable by a database. For example, computer-readable media include (but are not limited to) RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile discs (DVD), holographic media or other optical disc storage, magnetic cassettes, magnetic tape, magnetic disk storage, and other magnetic storage devices. These technologies can store data temporarily or permanently. However, unless explicitly specified otherwise, the term “computer-readable media” should not be construed to include physical, but transitory, forms of signal transmission such as radio broadcasts, electrical signals through a wire, or light pulses through a fiber-optic cable. Examples of stored information include computer-useable instructions, data structures, program modules, and other data representations.
Finally, network interface card (NIC) 624 is also attached to system bus 604 and allows computer 602 to communicate over a network such as network 626. NIC 624 can be any form of network interface known in the art, such as Ethernet, ATM, fiber, Bluetooth, or Wi-Fi (i.e., the Institute of Electrical and Electronics Engineers (IEEE) 802.11 family of standards). NIC 624 connects computer 602 to local network 626, which may also include one or more other computers, such as computer 628, and network storage, such as data store 630. Generally, a data store such as data store 630 may be any repository from which information can be stored and retrieved as needed. Examples of data stores include relational or object-oriented databases, spreadsheets, file systems, flat files, directory services such as LDAP and Active Directory, or email storage systems. A data store may be accessible via a complex API (such as, for example, Structured Query Language), a simple API providing only read, write and seek operations, or any level of complexity in between. Some data stores may additionally provide management functions for data sets stored therein such as backup or versioning. Data stores can be local to a single computer such as computer 628, accessible on a local network such as local network 626, or remotely accessible over public Internet 632. Local network 626 is in turn connected to public Internet 632, which connects many networks such as local network 626, remote network 634 or directly attached computers such as computer 636. In some embodiments, computer 602 can itself be directly connected to public Internet 632.
One or more aspects or features of the subject matter described herein can be realized in digital electronic circuitry, integrated circuitry, specially designed application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) computer hardware, firmware, software, and/or combinations thereof. These various aspects or features can include implementation in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which can be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device. The programmable system or computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
These computer programs, which can also be referred to as programs, software, software applications, applications, components, or code, include machine instructions for a programmable processor, and can be implemented in a high-level procedural language, an object-oriented programming language, a functional programming language, a logical programming language, and/or in assembly/machine language. As used herein, the term “computer-readable medium” refers to any computer program product, apparatus and/or device, such as for example magnetic discs, optical disks, memory, and Programmable Logic Devices (PLDs), used to provide machine instructions and/or data to a programmable processor, including a computer-readable medium that receives machine instructions as a computer-readable signal. The term “computer-readable signal” refers to any signal used to provide machine instructions and/or data to a programmable processor. The computer-readable medium can store such machine instructions non-transitorily, such as for example as would a non-transient solid-state memory or a magnetic hard drive or any equivalent storage medium. The computer-readable medium can alternatively or additionally store such machine instructions in a transient manner, for example as would a processor cache or other random-access memory associated with one or more physical processor cores.
Many different arrangements of the various components depicted, as well as components not shown, are possible without departing from the scope of the claims below. Embodiments have been described with the intent to be illustrative rather than restrictive. Alternative embodiments will become apparent to readers of this disclosure after and because of reading it. Alternative means of implementing the aforementioned can be completed without departing from the scope of the claims below. Certain features and sub-combinations are of utility and may be employed without reference to other features and sub-combinations and are contemplated within the scope of the claims. Although the present teachings have been described with reference to the embodiments illustrated in the attached drawing figures, it is noted that equivalents may be employed and substitutions made herein without departing from the scope of the claims.
| Number | Name | Date | Kind |
|---|---|---|---|
| 20130166919 | Thomsen | Jun 2013 | A1 |
| 20170249472 | Levy | Aug 2017 | A1 |
| 20210216661 | Pai | Jul 2021 | A1 |
| Number | Date | Country | |
|---|---|---|---|
| 20230188327 A1 | Jun 2023 | US |
