Partitioning online databases

The present invention extends to methods, systems, and computer program products for partitioning online databases. Online database operations, such as, for example, SPLIT, MERGE, and DROP, are used to alter the arrangement of partitions in a federated database. A SPLIT operation splits rows at one partition across a plurality of other partitions. A MERGE operation merges rows at a plurality of partitions in to one partition. A DROP operation shifts responsibility for rows of data from one partition to another partition and then drops the rows from the one partition.

CLUSTER RESTORE AND REBUILD

Architecture that facilitates the restoration of a cluster database in a scalable way using backups (e.g., SQL database backups) and a partition rebuild mechanism to achieve a high level of partition level data consistency, even when restore fails on individual machines and/or machine failure occurs. The architecture restores replicas of the partitions in consideration that the backups may be created at different points and at different times. Optimized parallelism is achieved in restoring each database machine using local backups, which eliminates cross-machine network traffic. Thus, fast recovery of the distributed database can be accomplished on the order of hours over thousands of machines and terabytes of data.

Quorum Based Transactionally Consistent Membership Management in Distributed Storage

Systems and methods that restore a failed reconfiguration of nodes in a distributed environment. By analyzing reports from read/write quorums of nodes associated with a configuration, automatic recovery for data partitions can be facilitated. Moreover, a configuration manager component tracks current configurations for replication units and determines whether a reconfiguration is required (e.g., due to node failures, node recovery, replica additions/deletions, replica moves, or replica role changes, and the like.) Reconfigurations of data activated as being replicated from an old configuration to being replicated on a new configuration may be performed in a transactionally consistent manner based on dynamic quorums associated with the new configuration and the old configuration. 1. A computer system comprising:a network; a configuration manager;', 'a current configuration comprising a first set of nodes; and', determining a version identifier associated with the new configuration;', 'updating transactions stored on the new configuration with transactions stored on the current configuration;', 'deactivating the current configuration;', 'activating the new configuration; and', 'committing the new configuration., 'a new configuration comprising a second set of nodes, the second set of nodes comprising a primary node, the primary node configured with computer executable instructions, that when executed on at least one processor on the primary node, implement a method of reconfiguring at least a portion of a distributed database replicated on the first set of nodes in the first configuration to being replicated on the second set of nodes in the new configuration, the at least a portion of a distributed database storing a plurality of transactions, the method comprising], 'a plurality of nodes connected to the network, the plurality of nodes comprising2. The system of claim 1 , wherein:each configuration of the current configuration and the new configuration is associated ...

Proactive failure handling in data processing systems

Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in computer network nodes. In an embodiment, a computer system monitors various health indicators for multiple nodes in a computer network. The computer system accesses stored health indicators that provide a health history for the computer network nodes. The computer system then generates a health status based on the monitored health indicators and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity.

Method and system for creating a database table index using multiple processors

A method and system for creating an index for a database table of records in a computer environment having a plurality of processing units wherein each processing unit has access to the database table. The method first determines partition delimiters wherein each partition delimiter separates the database table into non-overlapping partitions of records. Each of these partitions is dedicated to one processing unit for index creation. Next, each processing unit independently creates a sub-index, i.e., different processing units create at least two sub-indexes. Last, the method merges the sub-indexes together to create a final index related to the database table.

PROACTIVE FAILURE HANDLING IN NETWORK NODES

Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in computer network nodes. In an embodiment, a computer system monitors various health indicators for multiple nodes in a computer network. The computer system accesses stored health indicators that provide a health history for the computer network nodes. The computer system then generates a health status based on the monitored health factors and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity.

Dynamically varying the number of database replicas

Embodiments of the invention dynamically vary the number of replicas based on certain conditions to protect users from data loss. The size of the database is one condition that can be used to determine the number of replicas required. A database system may create three replicas. When the database size exceeds a first threshold, a fourth replica may be created. The fourth replica is maintained as long as the database size is above a second threshold that is smaller than the first threshold. However, when the database shrinks below the second threshold, then the fourth replica is deleted. Using two different thresholds in this manner prevents the system from frequently cycling between three and four replicas.

DEFRAGMENTING CLUSTERS WITH RESERVED RESOURCES

Defragmenting a cluster service to service additional capacity requests on the service. A method includes determining an amount of server resources needed for an additional deployment reservation request for a new deployment or increasing reservation of resources of an existing deployment. The method further includes determining a server that currently does not have capacity to service the additional deployment reservation request. The method further includes determining how resources on the server can be freed up by moving other replicas of other deployments on the server to other servers to allow the server to service the additional deployment reservation request. 1. In a distributed computing environment , a method of defragmenting a cluster service to service additional capacity requests on the cluster service , the method comprising:ranking servers in a cluster by free capacity and selecting a first server with the most free capacity;identifying one or more replicas from the selected first server to move to another server;determining the another server to which the one or more replicas from the first server can be moved by ranking other servers by available capacity and determining to move at least one replica of the one or more replicas to a server with a least actual capacity that could fit the one or more identified replicas; andmoving the one or more replicas to the server with the least actual capacity that could fit the one or more identified replicas.2. The method of claim 1 , wherein the at least one replica is moved to said another server that is also determined to be on a different upgrade domain than the first server.3. The method of claim 1 , wherein the at least one replica is moved to said another server that is also determined to be on a different fault domain than the first server.4. The method of claim 1 , further comprising:determining to move a particular replica of the one or more replicas based at least on a cost of moving the particular ...

Differential overbooking in a cloud computing environment

Techniques for differential overbooking on a cloud database. These techniques may include determining a reservation amount of a multi-tenant resource for a first service of a based upon an overbooking characteristic of the first service, and determining that a total usage value of the multi-tenant resource by a plurality of services is greater than a threshold value. In addition, the techniques may include determining a service usage value of the multi-tenant resource by the first service, determining a first overage value of the first service based on the service usage value and the reservation amount, and performing a resource reclamation process over the multi-tenant resource based on the first overage value of the first service.

Proactive failure handling in network nodes

Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in computer network nodes. In an embodiment, a computer system monitors various health indicators for multiple nodes in a computer network. The computer system accesses stored health indicators that provide a health history for the computer network nodes. The computer system then generates a health status based on the monitored health factors and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity.

Systems and methods for fragment-based serialization

A method and system for fragment-based serialization places one or more object members in fragments. Fragments may comprise a header and a payload. A header can provide useful information about the fragment, such as an indication of fragment type and an indication of fragment length. A payload may comprise one or more members of an object. Primitive members may be stored in a Binary Fragment with a record format payload. LOB and FS members may be stored in fragments that have a Value Type field for setting forth additional properties of the fragment. Collections may be stored in a series of fragments, a first fragment to indicate a start of a collection, one or more second fragments to serialize collection elements, and a Terminator Fragment to indicate the end of a collection. Fragment-serialized objects minimize storage overhead while providing fast instantiation and low-cost location and updating.

Quorum based transactionally consistent membership management in distributed storage

Systems and methods that restore a failed reconfiguration of nodes in a distributed environment. By analyzing reports from read/write quorums of nodes associated with a configuration, automatic recovery for data partitions can be facilitated. Moreover, a configuration manager component tracks current configurations for replication units and determines whether a reconfiguration is required (e.g., due to node failures, node recovery, replica additions/deletions, replica moves, or replica role changes, and the like.) Reconfigurations of data activated as being replicated from an old configuration to being replicated on a new configuration may be performed in a transactionally consistent manner based on dynamic quorums associated with the new configuration and the old configuration.

Memory management for multiple process instances

Intelligent memory brokering for multiple process instances, such as relational databases (e.g., SQL servers), reclaims memory based on value, thereby minimizing cost across instances. An exemplary solution includes: based at least on a trigger event, determining a memory profile for each of a plurality of process instances at a computing node; determining an aggregate memory profile, the aggregate memory profile indicating a memory unit cost for each of a plurality of memory units; determining a count of memory units to be reclaimed; identifying, based at least on the aggregate memory profile and the count of memory units to be reclaimed, a count of memory units to be reclaimed within each process instance so that a total cost is minimized to reclaim the determined count; and communicating, to each process instance having identified memory units to be reclaimed, a count of memory units to be reclaimed within the process instance.

Quorum based transactionally consistent membership management in distributed storage

Systems and methods that restore a failed reconfiguration of nodes in a distributed environment. By analyzing reports from read/write quorums of nodes associated with a configuration, automatic recovery for data partitions can be facilitated. Moreover, a configuration manager component tracks current configurations for replication units and determines whether a reconfiguration is required (e.g., due to node failures, node recovery, replica additions/deletions, replica moves, or replica role changes, and the like.) Reconfigurations of data activated as being replicated from an old configuration to being replicated on a new configuration may be performed in a transactionally consistent manner based on dynamic quorums associated with the new configuration and the old configuration.

PROACTIVE FAILURE HANDLING IN DATA PROCESSING SYSTEMS

Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in computer network nodes. In an embodiment, a computer system monitors various health indicators for multiple nodes in a computer network. The computer system accesses stored health indicators that provide a health history for the computer network nodes. The computer system then generates a health status based on the monitored health indicators and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity.

Dynamic Deactivation of Cold Database in Database Service

Managing databases implemented in a cloud computing environment. A method includes detecting that a database implemented in the cloud computing environment is in a state of non-use. The method further includes as a result of detecting that a database implemented in the cloud computing environment is in a state of non-use, instantiating a workload in the cloud computing environment to deactivate the database. The workload is configured to store metadata for the database and database data remotely in cloud storage such that the database can be reactivated at a later time. 1. A computer system comprising:one or more processors; and detect that a database implemented in the cloud computing environment is in a state of non-use; and', 'as a result of detecting that a database implemented in the cloud computing environment is in a state of non-use, instantiate a workload in the cloud computing environment to deactivate the database, wherein the workload is configured to store metadata for the database and database data remotely in cloud storage such that the database can be reactivated at a later time., 'one or more computer-readable media having stored thereon instructions that are executable by the one or more processors to configure the computer system to manage databases implemented in a cloud computing environment, including instructions that are executable to configure the computer system to perform at least the following2. The computer system of claim 1 , wherein one or more computer-readable media further have stored thereon instructions that are executable by the gone or more processors to configure the computer system to reactivate the database.3. The computer system of claim 2 , wherein one or more computer-readable media further have stored thereon instructions that are executable by the one or more processors to configure the computer system to perform at least the following:detect user interaction directed at the database; andwherein reactivating the database ...

PROACTIVE FAILURE HANDLING IN NETWORK NODES

Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in computer network nodes. In an embodiment, a computer system monitors various health indicators for multiple nodes in a computer network. The computer system accesses stored health indicators that provide a health history for the computer network nodes. The computer system then generates a health status based on the monitored health factors and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity. 1. A computer system for predicting the health of a plurality of data processing systems by using health report data , the computer system comprising one or more processors executing computer executable instructions which cause the computer system to perform the following:monitors one or more health indicators for a plurality of data processing systems;accesses one or more stored health indicators that provide a health history for one or more of the monitored plurality of data processing systems;based on both the monitored health factors and the stored health history, predicts a health status, wherein the predicted health status indicates for at least one of the monitored plurality of data processing systems a probability that the at least one monitored data processing system will be healthy within a specified future time period; andpresents the predicted health status to a specified entity.2. The computer system of claim 1 , wherein the computer system further performs the following:makes a determination that the probability that the at least one monitored data processing system will be healthy is below a threshold level; andtransfers one or more portions of data ...

Systems and methods for fragment-based serialization

A method and system for fragment-based serialization places one or more object members in fragments. Fragments may comprise a header and a payload. A header can provide useful information about the fragment, such as an indication of fragment type and an indication of fragment length. A payload may comprise one or more members of an object. Primitive members may be stored in a Binary Fragment with a record format payload. LOB and FS members may be stored in fragments that have a Value Type field for setting forth additional properties of the fragment. Collections may be stored in a series of fragments, a first fragment to indicate a start of a collection, one or more second fragments to serialize collection elements, and a Terminator Fragment to indicate the end of a collection. Fragment-serialized objects minimize storage overhead while providing fast instantiation and low-cost location and updating.

QUORUM BASED TRANSACTIONALLY CONSISTENT MEMBERSHIP MANAGEMENT IN DISTRIBUTED STORAGE SYSTEMS

Systems and methods that restore a failed reconfiguration of nodes in a distributed environment. By analyzing reports from read/write quorums of nodes associated with a configuration, automatic recovery for data partitions can be facilitated. Moreover, a configuration manager component tracks current configurations for replication units and determines whether a reconfiguration is required (e.g., due to node failures, node recovery, replica additions/deletions, replica moves, or replica role changes, and the like.) Reconfigurations of data activated as being replicated from an old configuration to being replicated on a new configuration may be performed in a transactionally consistent manner based on dynamic quorums associated with the new configuration and the old configuration.

Memory management for serverless databases

A solution is disclosed for memory management of serverless databases that includes: based at least on detecting a trigger event, determining whether memory is to be reclaimed; based at least on determining that memory is to be reclaimed, determining an amount of memory to be reclaimed; identifying memory to be reclaimed; and reclaiming the identified memory. Disclosed solutions are flexible, enabling customization of the aggressiveness and manner of memory reclamation. This permits users to specify a tailored balance point between performance and cost, for arrangements that bill users based on resource usage (e.g., memory consumed by a serverless database). In some examples, users specify a ramp-down parameter that is used to determine how much memory can be evicted in a particular reclamation event, time intervals (or another criteria) for triggering a reclamation event, and a definition for whether a cache is active.

CONFIGURATION MANAGEMENT IN DISTRIBUTED DATA SYSTEMS

Systems and methods for managing configurations of data nodes in a distributed environment A configuration manager is implemented as a set of distributed master nodes that may use quorum-based processing to enable reliable identification of master nodes storing current configuration information, even if some of the master nodes fail. If a quorum of master nodes cannot be achieved or some other event occurs that precludes identification of current configuration information, the configuration manager may be rebuilt by analyzing reports from read/write quorums of nodes associated with a configuration, allowing automatic recovery of data partitions.

Auto-parameterization of database queries

An auto-parameterization process transforms a database query into a parameterized basic query form by replacing any constant values in the query with parameters. The auto-parameterization process attempts to generate a safe execution plan from the basic query form if there is currently no such plan available. A safe execution plan is defined as an execution plan that is optimal over a range of values for the parameters. If a safe execution plan can be generated, it is passed for execution, along with the constant values that were present in the query. If a safe execution plan cannot be generated, the auto-parameterization process passes a specific execution plan for execution. The safe execution plan is cached either at the time it is created or at the time it is executed. The cache is searched each time a parameterized basic query plan is generated by the auto-parameterization process. The auto-parameterization process also evaluates the query before creating the corresponding parameterized ...

Systems and methods for fragment-based serialization

A method and system for fragment-based serialization places one or more object members in fragments. Fragments may comprise a header and a payload. A header can provide useful information about the fragment, such as an indication of fragment type and an indication of fragment length. A payload may comprise one or more members of an object. Primitive members may be stored in a Binary Fragment with a record format payload. LOB and FS members may be stored in fragments that have a Value Type field for setting forth additional properties of the fragment. Collections may be stored in a series of fragments, a first fragment to indicate a start of a collection, one or more second fragments to serialize collection elements, and a Terminator Fragment to indicate the end of a collection. Fragment-serialized objects minimize storage overhead while providing fast instantiation and low-cost location and updating.

DEFRAGMENTING CLUSTERS WITH RESERVED RESOURCES

Defragmenting a cluster service to service additional capacity requests on the service. A method includes determining an amount of server resources needed for an additional deployment reservation request for a new deployment or increasing reservation of resources of an existing deployment. The method further includes determining a server that currently does not have capacity to service the additional deployment reservation request. The method further includes determining how resources on the server can be freed up by moving other replicas of other deployments on the server to other servers to allow the server to service the additional deployment reservation request. 1. In a distributed computing environment , a method of defragmenting a cluster service to service additional capacity requests on the service the method comprising:determining an amount of server resources needed for an additional deployment reservation request for a new deployment or increasing reservation of resources of an existing deployment;determining a server that currently does not have capacity to service the additional deployment reservation request; anddetermining how resources on the server can be freed up by moving other replicas of other deployments on the server to other servers to allow the server to service the additional deployment reservation request.2. The method of claim 1 , wherein the additional deployment reservation request is an upgrade request to reserve additional resources for an existing deployment.3. The method of claim 1 , wherein the additional deployment reservation request is a new deployment request requesting a reservation of resources for a new deployment.4. The method of claim 1 , wherein determining that resources on the server can be freed up by moving other replicas of other deployments comprises following rules for a fault domain.5. The method of claim 1 , wherein determining that resources on the server can be freed up by moving other replicas of other ...

QUORUM BASED TRANSACTIONALLY CONSISTENT MEMBERSHIP MANAGEMENT IN DISTRIBUTED STORAGE

Systems and methods that restore a failed reconfiguration of nodes in a distributed environment. By analyzing reports from read/write quorums of nodes associated with a configuration, automatic recovery for data partitions can be facilitated. Moreover, a configuration manager component tracks current configurations for replication units and determines whether a reconfiguration is required (e.g., due to node failures, node recovery, replica additions/deletions, replica moves, or replica role changes, and the like.) Reconfigurations of data activated as being replicated from an old configuration to being replicated on a new configuration may be performed in a transactionally consistent manner based on dynamic quorums associated with the new configuration and the old configuration. 120-. (canceled)21. A computing device , comprising: determining an identifier associated with the second configuration;', 'updating transactions stored on the second configuration with transactions stored on the first configuration;', 'transitioning from the first configuration to the second configuration; and', 'wherein the proceeding operations are performed in response to acceptances from at least a quorum number of nodes on which the operations are proposed to be performed., 'a memory and a processor that are respectively configured to store and execute instructions, including instructions for causing the computing device to perform operations for reconfiguring at least a portion of a distributed system including a first set of nodes in a first configuration to a second set of nodes in a second configuration, the at least the portion of the distributed system storing a plurality of transactions, the operations including22. The computing device of claim 21 , wherein: selecting the identifier associated with the second configuration;', 'sending to each of a plurality of nodes in the first configuration and to each of a plurality of nodes in the second configuration a reconfiguration ...

SEAMLESS UPGRADES IN A DISTRIBUTED DATABASE SYSTEM

Embodiments are directed to providing distributed database service upgrades of database server instances in a computer cluster using multiple database server instances and to monitoring and maintaining a distributed database service during upgrade. In an embodiment, each computer system in a computer cluster instantiates at least two different database server instances on each of the nodes in the cluster. The first database server instances are configured to operate using a current distributed database version and the second instances are configured to operate using a new, updated distributed database service version. The computer system receives an indication that the distributed database service is to be upgraded. Then, based on the received indication, the computer system migrates database replicas from the first database server instances to the second database server instances which operate the new, updated service version, substantially without user-visible downtime. 1. At a distributed database system including at least one processor and a memory , in a computer networking environment including a plurality of computing systems , a computer-implemented method for providing distributed database service upgrades using multiple database server instances , the method comprising:an act of instantiating a plurality of first and second database server instances on each of a plurality of computer systems in a database cluster, including a primary node and at least a first secondary node, wherein the first database server instances are each running a current distributed database service version and the second database server instances are simultaneously each running a new distributed database service version;an act of receiving an indication that the distributed database service is to be upgraded; andbased on the received indication, an act of migrating database replicas from the first database server instances to the second database server instances, substantially ...

PARTITIONING ONLINE DATABASES

The present invention extends to methods, systems, and computer program products for partitioning online databases. Online database operations, such as, for example, SPLIT, MERGE, and DROP, are used to alter the arrangement of partitions in a federated database. A SPLIT operation splits rows at one partition across a plurality of other partitions. A MERGE operation merges rows at a plurality of partitions in to one partition. A DROP operation shifts responsibility for rows of data from one partition to another partition and then drops the rows from the one partition.

DIFFERENTIAL OVERBOOKING IN A CLOUD COMPUTING ENVIRONMENT

Techniques for differential overbooking on a cloud database. These techniques may include determining a reservation amount of a multi-tenant resource for a first service of a based upon an overbooking characteristic of the first service, and determining that a total usage value of the multi-tenant resource by a plurality of services is greater than a threshold value. In addition, the techniques may include determining a service usage value of the multi-tenant resource by the first service, determining a first overage value of the first service based on the service usage value and the reservation amount, and performing a resource reclamation process over the multi-tenant resource based on the first overage value of the first service.

Dynamically Varying the Number of Database Replicas

Embodiments of the invention dynamically vary the number of replicas based on certain conditions to protect users from data loss. The size of the database is one condition that can be used to determine the number of replicas required. A database system may create three replicas. When the database size exceeds a first threshold, a fourth replica may be created. The fourth replica is maintained as long as the database size is above a second threshold that is smaller than the first threshold. However, when the database shrinks below the second threshold, then the fourth replica is deleted. Using two different thresholds in this manner prevents the system from frequently cycling between three and four replicas.

Defragmenting clusters with reserved resources

Defragmenting a cluster service to service additional capacity requests on the service. A method includes determining an amount of server resources needed for an additional deployment reservation request for a new deployment or increasing reservation of resources of an existing deployment. The method further includes determining a server that currently does not have capacity to service the additional deployment reservation request. The method further includes determining how resources on the server can be freed up by moving other replicas of other deployments on the server to other servers to allow the server to service the additional deployment reservation request.

Proactive failure handling in data processing systems

Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in computer network nodes. In an embodiment, a computer system monitors various health indicators for multiple nodes in a computer network. The computer system accesses stored health indicators that provide a health history for the computer network nodes. The computer system then generates a health status based on the monitored health factors and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity.

Method and system for creating a database table index using multiple processors

A method and system for creating an index for a database table of records in a computer environment having a plurality of processing units wherein each processing unit has access to the database table. The method first determines partition delimiters wherein each partition delimiter separates the database table into non-overlapping partitions of records. Each of these partitions is dedicated to one processing unit for index creation. Next, each processing unit independently creates a sub-index, i.e., different processing units create at least two sub-indexes. Last, the method merges the sub-indexes together to create a final index related to the database table.

System and method for determining cache activity and optimizing cache reclamation

Methods for determining cache activity and for optimizing cache reclamation are performed by systems and devices. A cache entry access is determined at an access time, and a data object of the cache entry for a current time window is identified that includes a time stamp for a previous access and a counter index. A conditional counter operation is then performed on the counter associated with the index to increment the counter when the time stamp is outside the time window or to maintain the counter when the time stamp is within the time window. A counter index that identifies another counter for a previous time window where the other counter value was incremented for the previous cache entry access causes the other counter to be decremented. A cache configuration command to reclaim, or additionally allocate space to, the cache is generated based on the values of the counters.

SCOPED DATABASE CONNECTIONS

The present invention extends to methods, systems, and computer program products for scoping the context used to access a database partition. Embodiments of the invention enable data isolation using partitions in multi-tenant databases, while relieving client applications from dealing with the partitions. For example, a computer system that includes a distributed database system comprising a plurality of database partitions in a federation receives a context to use when performing database access operations within the distributed database system. The context identifies specified relevant portion of the federation. The computer system also receives a database access operation that is associated with the context. The computer system modifies the semantics of the database access operation in accordance with the associated context, to direct application of the database access operation to the specified relevant portion of the federation.

Systems and methods for a large object infrastructure in a database system

Various embodiments of the present invention are direct to the utilization of Blob Handles (BHs) which are an internal representation of a large value. BHs are immutable and stateless references to a large data object. The structure of a BH contains enough information to return an ILockBytes interface in order to provide access to the corresponding large data block, and a BH can also return information regarding its own lifetime description. A BH can be completely described using (a) a pointer to the beginning of BH data and (b) the byte-length of the BH.

QUORUM BASED TRANSACTIONALLY CONSISTENT MEMBERSHIP MANAGEMENT IN DISTRIBUTED STORAGE

Systems and methods that restore a failed reconfiguration of nodes in a distributed environment. By analyzing reports from read/write quorums of nodes associated with a configuration, automatic recovery for data partitions can be facilitated. Moreover, a configuration manager component tracks current configurations for replication units and determines whether a reconfiguration is required (e.g., due to node failures, node recovery, replica additions/deletions, replica moves, or replica role changes, and the like.) Reconfigurations of data activated as being replicated from an old configuration to being replicated on a new configuration may be performed in a transactionally consistent manner based on dynamic quorums associated with the new configuration and the old configuration. 120-. (canceled)21. A computing device , comprising: determining an identifier associated with the second configuration;', 'updating transactions stored on the second configuration with transactions stored on the first configuration;', 'deactivating the first configuration; and', 'activating the second configuration;', 'wherein each of the proceeding operations is performed in response to receiving responses indicating acceptance of that operation from at least a quorum number of nodes on which that operation is proposed to be performed., 'a memory and a processor that are respectively configured to store and execute instructions, including instructions for causing the computing device to perform operations for reconfiguring at least a portion of a distributed system including a first set of nodes in a first configuration to a second set of nodes in a second configuration, the at least the portion of the distributed system storing a plurality of transactions, the operations including22. The computing device of claim 21 , wherein: selecting the identifier associated with the second configuration;', 'sending to each of a plurality of nodes in the first configuration and to each of a plurality ...

Partitioning online databases

Methods, systems, and computer program products are provided for partitioning online databases. Online database operations, such as, for example, SPLIT, MERGE, and DROP, are used to alter the arrangement of partitions in a federated database. A SPLIT operation splits rows at one partition across a plurality of other partitions. A MERGE operation merges rows at a plurality of partitions in to one partition. A DROP operation shifts responsibility for rows of data from one partition to another partition and then drops the rows from the one partition.

Dynamic deactivation of cold database in database service

Managing databases implemented in a cloud computing environment. A method includes detecting that a database implemented in the cloud computing environment is in a state of non-use. The method further includes as a result of detecting that a database implemented in the cloud computing environment is in a state of non-use, instantiating a workload in the cloud computing environment to deactivate the database. The workload is configured to store metadata for the database and database data remotely in cloud storage such that the database can be reactivated at a later time.

PARTITIONING ONLINE DATABASES

Methods, systems, and computer program products are provided for partitioning online databases. Online database operations, such as, for example, SPLIT, MERGE, and DROP, are used to alter the arrangement of partitions in a federated database. A SPLIT operation splits rows at one partition across a plurality of other partitions. A MERGE operation merges rows at a plurality of partitions in to one partition. A DROP operation shifts responsibility for rows of data from one partition to another partition and then drops the rows from the one partition. 1. A computing system , comprising:one or more processors; and receive a drop directive including a set of key values that each identify a different row of the distributed database that is to be dropped, the set of key values identifying: (i) one or more first rows selected from among a first subset of rows that are stored in a first partition of the distributed database, and (ii) one or more second rows selected from among a second subset of rows that are stored in a second partition of the distributed database; and', creating a third partition of the distributed database;', 'expanding the one or more first rows and the one or more second rows into the third partition; and', 'dropping the one or more first rows from the first partition and dropping the one or more second rows from the second partition., 'execute a drop operation to drop the one or more first rows and the rows one or more second rows, while the first and second partitions remain online, including], 'one or more computer-readable media having stored thereon computer-executable instructions that are executable by the one or more processors to cause the computing system to drop rows in a distributed database, the computer-executable instructions including instructions that are executable to cause the computing system to perform at least the following2. The computing system of claim 1 , the computer-executable instructions also including instructions that are ...

Seamless upgrades in a distributed database system

Embodiments are directed to providing distributed database service upgrades of database server instances in a computer cluster using multiple database server instances and to monitoring and maintaining a distributed database service during upgrade. In an embodiment, each computer system in a computer cluster instantiates at least two different database server instances on each of the nodes in the cluster. The first database server instances are configured to operate using a current distributed database version and the second instances are configured to operate using a new, updated distributed database service version. The computer system receives an indication that the distributed database service is to be upgraded. Then, based on the received indication, the computer system migrates database replicas from the first database server instances to the second database server instances which operate the new, updated service version, substantially without user-visible downtime.

Dynamically varying the number of database replicas

Embodiments of the invention dynamically vary the number of replicas based on certain conditions to protect users from data loss. The size of the database is one condition that can be used to determine the number of replicas required. A database system may create three replicas. When the database size exceeds a first threshold, a fourth replica may be created. The fourth replica is maintained as long as the database size is above a second threshold that is smaller than the first threshold. However, when the database shrinks below the second threshold, then the fourth replica is deleted. Using two different thresholds in this manner prevents the system from frequently cycling between three and four replicas.

Quorum based transactionally consistent membership management in distributed storage systems

Systems and methods that restore a failed reconfiguration of nodes in a distributed environment. By analyzing reports from read/write quorums of nodes associated with a configuration, automatic recovery for data partitions can be facilitated. Moreover, a configuration manager component tracks current configurations for replication units and determines whether a reconfiguration is required (e.g., due to node failures, node recovery, replica additions/deletions, replica moves, or replica role changes, and the like.) Reconfigurations of data activated as being replicated from an old configuration to being replicated on a new configuration may be performed in a transactionally consistent manner based on dynamic quorums associated with the new configuration and the old configuration.

PARTITIONING ONLINE DATABASES

Methods, systems, and computer program products are provided for partitioning online databases. Online database operations, such as, for example, SPLIT, MERGE, and DROP, are used to alter the arrangement of partitions in a federated database. A SPLIT operation splits rows at one partition across a plurality of other partitions. A MERGE operation merges rows at a plurality of partitions in to one partition. A DROP operation shifts responsibility for rows of data from one partition to another partition and then drops the rows from the one partition. 1. At a distributed database system including one or more processors and system memory , the distributed database system also including a plurality of database partitions , including a first database partition and a second database partition , in a federation , the federation configured to store a plurality of rows of data , each row of data identified by a federation key value such that the federation stores data for a set of federation key values , each of the plurality of database partitions configured to store any rows of data having a federation key values within a specified subset of the set of federation key values , a method for dropping rows of data from the distributed database system , the method comprising:an act of receiving a partition drop directive indicating how to process at least some of one or more of the plurality of specified subsets of federation key values to drop corresponding rows of data stored in the plurality of database partitions; andan act of executing a drop operation to drop the corresponding rows of data in accordance with the partition drop directive and while the plurality of database partitions remain online, including for each database partition that is to drop corresponding rows of data, configuring one or more other database partitions to store portions of the rows of data to be dropped.2. The method of claim 1 , wherein configuring another database to store portions of the rows of ...

Proactive failure handling in database services

Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in database services. In an embodiment, a computer system monitors various health indicators for multiple nodes in a database cluster. The computer system accesses stored health indicators that provide a health history for the database cluster nodes. The computer system then generates a health status based on the monitored health factors and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity.

Modeling and Forecasting Reserve Capacity for Overbooked Clusters

Managing cluster resources for a cluster. The method includes identifying a plurality of quiescence policies. Each of the quiescence policies define one or more conditions for cluster entities which when met, identify that cluster resources should be reclaimed from cluster entities by quiescing cluster entities. The method further includes, for each quiescence policy, identifying an amount of reclaimed capacity defining the amount of cluster resources that will be reclaimed by implementing the quiescence policy. The method further includes, for each quiescence policy, identifying an amount of reserve capacity defining the amount of cluster resources that should be reserved for resuming quiesced cluster entities. The method further includes; selecting a quiescence policy based on comparing the reclaimed capacities and reserve capacities for the quiescence policies. The method further includes, booking cluster resources for cluster entities on the cluster according to the selected quiescence policy 1. A computer system comprising:one or more processors; and identify a plurality of quiescence policies, wherein each of the quiescence policies define one or more conditions for cluster entities which when met, identify that cluster resources should be reclaimed from cluster entities by quiescing cluster entities;', 'for each quiescence policy in the plurality of quiescence policies, identify an amount of reclaimed capacity defining the amount of cluster resources that will be reclaimed by implementing the quiescence policy;', 'for each quiescence policy in the plurality of quiescence policies, identify an amount of reserve capacity defining the amount of cluster resources that should be reserved for resuming quiesced cluster entities;', 'select a quiescence policy from among the plurality of quiescence policies based on comparing the reclaimed capacities and reserve capacities for the quiescence policies in the plurality of quiescence policies; and', 'book cluster ...

Systems and methods for a large object infrastructure in a database system

Various embodiments of the present invention are direct to the utilization of Blob Handles (BHs) which are an internal representation of a large value. BHs are immutable and stateless references to a large data object. The structure of a BH contains enough information to return an ILockBytes interface in order to provide access to the corresponding large data block, and a BH can also return information regarding its own lifetime description. A BH can be completely described using (a) a pointer to the beginning of BH data and (b) the byte-length of the BH.

Defragmenting clusters with reserved resources

Defragmenting a cluster service to service additional capacity requests on the service. A method includes determining an amount of server resources needed for an additional deployment reservation request for a new deployment or increasing reservation of resources of an existing deployment. The method further includes determining a server that currently does not have capacity to service the additional deployment reservation request. The method further includes determining how resources on the server can be freed up by moving other replicas of other deployments on the server to other servers to allow the server to service the additional deployment reservation request.

Scoped database connections

The present invention extends to methods, systems, and computer program products for scoping the context used to access a database partition. Embodiments of the invention enable data isolation using partitions in multi-tenant databases, while relieving client applications from dealing with the partitions. For example, a computer system that includes a distributed database system comprising a plurality of database partitions in a federation receives a context to use when performing database access operations within the distributed database system. The context identifies specified relevant portion of the federation. The computer system also receives a database access operation that is associated with the context. The computer system modifies the semantics of the database access operation in accordance with the associated context, to direct application of the database access operation to the specified relevant portion of the federation.

Memory management for multiple process instances

Intelligent memory brokering for multiple process instances, such as relational databases (e.g., SQL servers), reclaims memory based on value, thereby minimizing cost across instances. An exemplary solution includes: based at least on a trigger event, determining a memory profile for each of a plurality of process instances at a computing node; determining an aggregate memory profile, the aggregate memory profile indicating a memory unit cost for each of a plurality of memory units; determining a count of memory units to be reclaimed; identifying, based at least on the aggregate memory profile and the count of memory units to be reclaimed, a count of memory units to be reclaimed within each process instance so that a total cost is minimized to reclaim the determined count; and communicating, to each process instance having identified memory units to be reclaimed, a count of memory units to be reclaimed within the process instance.

PROACTIVE FAILURE HANDLING IN DATABASE SERVICES

Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in database services. In an embodiment, a computer system monitors various health indicators for multiple nodes in a database cluster. The computer system accesses stored health indicators that provide a health history for the database cluster nodes. The computer system then generates a health status based on the monitored health factors and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity.

Dynamically Varying the Number of Database Replicas

Embodiments of the invention dynamically vary the number of replicas based on certain conditions to protect users from data loss. The size of the database is one condition that can be used to determine the number of replicas required. A database system may create three replicas. When the database size exceeds a first threshold, a fourth replica may be created. The fourth replica is maintained as long as the database size is above a second threshold that is smaller than the first threshold. However, when the database shrinks below the second threshold, then the fourth replica is deleted. Using two different thresholds in this manner prevents the system from frequently cycling between three and four replicas. 1. A computer-implemented method , comprising:creating three replicas for a database;monitoring a size of the database with respect to a first threshold;creating a fourth replica for the database when the size is greater than the first threshold;monitoring the size of the database with respect to a second threshold; anddeleting the fourth replica when the size of the database is less than the second threshold.2. The computer-implemented method of claim 1 , further comprising:creating the replicas on separate machines.3. The computer-implemented method of claim 1 , wherein one of the replicas is designated as a primary replica and the other replicas are secondary replicas.4. The computer-implemented method of claim 1 , wherein a partition manager controls the creation and deletion of the fourth replica.5. The computer-implemented method of claim 4 , wherein a load balancer agent monitors the database and provides database size data to the partition manager.6. The computer-implemented method of claim 4 , further comprising:maintaining a global partition map in the partition manager maintains to track replicas for a plurality of databases.7. The computer-implemented method of claim 2 , further comprising:maintaining a local partition map each machine to track the ...

System and method for determining cache activity and optimizing cache reclamation

Methods for determining cache activity and for optimizing cache reclamation are performed by systems and devices. A cache entry access is determined at an access time, and a data object of the cache entry for a current time window is identified that includes a time stamp for a previous access and a counter index. A conditional counter operation is then performed on the counter associated with the index to increment the counter when the time stamp is outside the time window or to maintain the counter when the time stamp is within the time window. A counter index that identifies another counter for a previous time window where the other counter value was incremented for the previous cache entry access causes the other counter to be decremented. A cache configuration command to reclaim, or additionally allocate space to, the cache is generated based on the values of the counters.

Memory management for multiple process instances

Intelligent memory brokering for multiple process instances, such as relational databases (e.g., SQL servers), reclaims memory based on value, thereby minimizing cost across instances. An exemplary solution includes: based at least on a trigger event, determining a memory profile for each of a plurality of process instances at a computing node; determining an aggregate memory profile, the aggregate memory profile indicating a memory unit cost for each of a plurality of memory units; determining a count of memory units to be reclaimed; identifying, based at least on the aggregate memory profile and the count of memory units to be reclaimed, a count of memory units to be reclaimed within each process instance so that a total cost is minimized to reclaim the determined count; and communicating, to each process instance having identified memory units to be reclaimed, a count of memory units to be reclaimed within the process instance.

PROACTIVE FAILURE HANDLING IN DATA PROCESSING SYSTEMS

Embodiments are directed to predicting the health of a computer node using health report data and to proactively handling failures in computer network nodes. In an embodiment, a computer system monitors various health indicators for multiple nodes in a computer network. The computer system accesses stored health indicators that provide a health history for the computer network nodes. The computer system then generates a health status based on the monitored health indicators and the health history. The generated health status indicates the likelihood that the node will be healthy within a specified future time period. The computer system then leverages the generated health status to handle current or predicted failures. The computer system also presents the generated health status to a user or other entity. 1monitor one or more health indicators for the one or more nodes;access one or more stored health indicators that provide a health history for the one or more monitored nodes;based at least on both the monitored one or more health indicators and the health history, predict a future health status for the one or more monitored nodes; andpresent the predicted future health status.. A computer system for predicting the health of one or more nodes, the computer system comprising one or more processors executing computer executable instructions which cause the computer system to: This application is a continuation of and claims benefit of U.S. patent application Ser. No. 15/392,387 entitled “PROACTIVE FAILURE HANDLING IN DATABASE SERVICES”, filed with the U.S. Patent and Trademark Office on Dec. 28, 2016, which is a continuation of and claims benefit of Ser. No. 15/088,377 entitled “PROACTIVE FAILURE HANDLING IN DATABASE SERVICES”, filed with the U.S. Patent and Trademark Office on Apr. 1, 2016, now U.S. Pat. No. 9,594,620, which is a continuation of and claims benefit of U.S. patent application Ser. No. 14/537,130 entitled “PROACTIVE FAILURE HANDLING IN NETWORK NODES”, ...

MEMORY MANAGEMENT FOR SERVERLESS DATABASES

A solution is disclosed for memory management of serverless databases that includes: based at least on detecting a trigger event, determining whether memory is to be reclaimed; based at least on determining that memory is to be reclaimed, determining an amount of memory to be reclaimed; identifying memory to be reclaimed; and reclaiming the identified memory. Disclosed solutions are flexible, enabling customization of the aggressiveness and manner of memory reclamation. This permits users to specify a tailored balance point between performance and cost, for arrangements that bill users based on resource usage (e.g., memory consumed by a serverless database). In some examples, users specify a ramp-down parameter that is used to determine how much memory can be evicted in a particular reclamation event, time intervals (or another criteria) for triggering a reclamation event, and a definition for whether a cache is active. 1. One or more computer storage devices having computer-executable instructions stored thereon for memory management of serverless databases , which , on execution by a computer , cause the computer to perform operations comprising: 'a timer event and a memory usage parameter exceeding a threshold;', 'detecting a trigger event for reclaiming memory from a serverless database instance, wherein the trigger event comprises at least one event selected from the list consisting of;'}receiving a selection defining at least a portion of a set of performance parameters;based at least on detecting the trigger event, determining whether memory is to be reclaimed, wherein determining whether memory is to be reclaimed comprises measuring the set of performance parameters;receiving a selection defining a ramp-down parameter;based at least on determining that memory is to be reclaimed, determining an amount of memory to be reclaimed, wherein determining an amount of memory to be reclaimed comprises calculating the amount of memory to be reclaimed using the ramp- ...

Memory management for multiple process instances

Intelligent memory brokering for multiple process instances, such as relational databases (e.g., SQL servers), reclaims memory based on value, thereby minimizing cost across instances. An exemplary solution includes: based at least on a trigger event, determining a memory profile for each of a plurality of process instances at a computing node; determining an aggregate memory profile, the aggregate memory profile indicating a memory unit cost for each of a plurality of memory units; determining a count of memory units to be reclaimed; identifying, based at least on the aggregate memory profile and the count of memory units to be reclaimed, a count of memory units to be reclaimed within each process instance so that a total cost is minimized to reclaim the determined count; and communicating, to each process instance having identified memory units to be reclaimed, a count of memory units to be reclaimed within the process instance.

Dynamic deactivation of cold database in database service

Managing databases implemented in a cloud computing environment. A method includes detecting that a database implemented in the cloud computing environment is in a state of non-use. The method further includes as a result of detecting that a database implemented in the cloud computing environment is in a state of non-use, instantiating a workload in the cloud computing environment to deactivate the database. The workload is configured to store metadata for the database and database data remotely in cloud storage such that the database can be reactivated at a later time.

Systems and methods for fragment-based serialization

A method and system for fragment-based serialization places one or more object members in fragments. Fragments may comprise a header and a payload. A header can provide useful information about the fragment, such as an indication of fragment type and an indication of fragment length. A payload may comprise one or more members of an object. Primitive members may be stored in a Binary Fragment with a record format payload. LOB and FS members may be stored in fragments that have a Value Type field for setting forth additional properties of the fragment. Collections may be stored in a series of fragments, a first fragment to indicate a start of a collection, one or more second fragments to serialize collection elements, and a Terminator Fragment to indicate the end of a collection. Fragment-serialized objects minimize storage overhead while providing fast instantiation and low-cost location and updating.

Dynamic deactivation of cold database in a database service

El manejar bases de datos implementado en un ambiente de cómputo de nube. Un método incluye detectar que una base de datos implementada en el ambiente de cómputo de nube está en un estado de no uso. El método también incluye como resultado de detectar que una base de datos implementada en el ambiente de cómputo de nube está en un estado de no uso, instanciar una carga de trabajo en el ambiente de cómputo de nube para desactivar la base de datos. La carga de trabajo está configurada para almacenar metadatos para la base de datos y los datos de la base de datos en forma remota en el almacenamiento de nube de modo que la base de datos se puede reactivar en un tiempo futuro.

Dynamic deactivation of cold database in database service

Managing databases implemented in a cloud computing environment. A method includes detecting that a database implemented in the cloud computing environment is in a state of non-use. The method further includes as a result of detecting that a database implemented in the cloud computing environment is in a state of non-use, instantiating a workload in the cloud computing environment to deactivate the database. The workload is configured to store metadata for the database and database data remotely in cloud storage such that the database can be reactivated at a later time.

Memory management for serverless databases

A solution is disclosed for memory management of serverless databases that includes: based at least on detecting a trigger event, determining whether memory is to be reclaimed; based at least on determining that memory is to be reclaimed, determining an amount of memory to be reclaimed; identifying memory to be reclaimed; and reclaiming the identified memory. Disclosed solutions are flexible, enabling customization of the aggressiveness and manner of memory reclamation. This permits users to specify a tailored balance point between performance and cost, for arrangements that bill users based on resource usage (e.g., memory consumed by a serverless database). In some examples, users specify a ramp-down parameter that is used to determine how much memory can be evicted in a particular reclamation event, time intervals (or another criteria) for triggering a reclamation event, and a definition for whether a cache is active.

System and method for managing cloud service resources in a cloud computing environment

Systems, methods, and devices are described for managing cloud services implemented by one or more clusters in a cloud computing environment. Responsive to receiving a first notification indicating that a cloud service implemented by the one or more clusters has not been used for a first predetermined amount of time, the cloud service is maintained in an active state and metadata is updated that specifies the cloud service is in a deactivated state. The metadata is visible to a user interface of a management portal of the cloud computing environment. Responsive to receiving a second notification indicating that the cloud service has not been used for a second predetermined amount of time following the first predetermined amount of time, a deactivation workflow is instantiated to deactivate the cloud service. In a further aspect, a cloud service engine generates the first and second notifications.

Memory management for multiple process instances

Intelligent memory brokering for multiple process instances, such as relational databases (e.g., SQL servers), reclaims memory based on value, thereby minimizing cost across instances. An exemplary solution includes: based at least on a trigger event, determining a memory profile for each of a plurality of process instances at a computing node; determining an aggregate memory profile, the aggregate memory profile indicating a memory unit cost for each of a plurality of memory units; determining a count of memory units to be reclaimed; identifying, based at least on the aggregate memory profile and the count of memory units to be reclaimed, a count of memory units to be reclaimed within each process instance so that a total cost is minimized to reclaim the determined count; and communicating, to each process instance having identified memory units to be reclaimed, a count of memory units to be reclaimed within the process instance.

Quorum based transactionally consistent membership management in distributed storage systems

Dynamic deactivation of cold database in database service

Managing databases implemented in a cloud computing environment. A method includes detecting that a database implemented in the cloud computing environment is in a state of non-use. The method further includes as a result of detecting that a database implemented in the cloud computing environment is in a state of non-use, instantiating a workload in the cloud computing environment to deactivate the database. The workload is configured to store metadata for the database and database data remotely in cloud storage such that the database can be reactivated at a later time.

Dynamic deactivation of cold database in database service

Managing databases implemented in a cloud computing environment. A method (200) includes detecting (202) that a database (115) implemented in the cloud computing environment is in a state of non-use. The method further includes as a result (204) of detecting that a database implemented in the cloud computing environment is in a state of non-use, instantiating a workload (120) in the cloud computing environment to deactivate the database. The workload is configured to store metadata (122) for the database and database data (124) remotely in cloud storage (126) such that the database can be reactivated at a later time.

Systems and methods for a large object infrastructure in a database system

System and method for managing cloud service resources in a cloud computing environment

Systems, methods, and devices are described for managing cloud services implemented by one or more clusters in a cloud computing environment. Responsive to receiving a first notification indicating that a cloud service implemented by the one or more clusters has not been used for a first predetermined amount of time, the cloud service is maintained in an active state and metadata is updated that specifies the cloud service is in a deactivated state. The metadata is visible to a user interface of a management portal of the cloud computing environment. Responsive to receiving a second notification indicating that the cloud service has not been used for a second predetermined amount of time following the first predetermined amount of time, a deactivation workflow is instantiated to deactivate the cloud service. In a further aspect, a cloud service engine generates the first and second notifications.

Exposing control to enable interactive schedulers for cloud cluster orchestration systems

Methods, systems, and computer program products are provided for a compute cluster comprising placement and load balancing (PLB) logic that receives data (e.g., state metadata) relating to a service (e.g., database service) executing on the compute cluster, from a resource manager executing on the compute cluster, via a first API associated with the resource manager. The PLB logic receives second data from the service via a second API and determines whether a PLB action is indicated based on one of the second data or a combination of the first data and the second data. When a PLB action is indicated, the PLB logic sends a command to the resource manager to execute the PLB action. The PLB logic also receives queries from clients external to the compute cluster and may spawn a child PLB logic to offload PLB operations, respond to queries, or perform software validation in the child.

Memory management for multiple process instances

Intelligent memory brokering for multiple process instances, such as relational databases (e.g., SQL servers), reclaims memory based on value, thereby minimizing cost across instances. An exemplary solution includes: based at least on a trigger event, determining a memory profile for each of a plurality of process instances at a computing node; determining an aggregate memory profile, the aggregate memory profile indicating a memory unit cost for each of a plurality of memory units; determining a count of memory units to be reclaimed; identifying, based at least on the aggregate memory profile and the count of memory units to be reclaimed, a count of memory units to be reclaimed within each process instance so that a total cost is minimized to reclaim the determined count; and communicating, to each process instance having identified memory units to be reclaimed, a count of memory units to be reclaimed within the process instance.

Memory management for multiple process instances

Intelligent memory brokering for multiple process instances, such as relational databases (e.g., SQL servers), reclaims memory based on value, thereby minimizing cost across instances. An exemplary solution includes: based at least on a trigger event, determining a memory profile for each of a plurality of process instances at a computing node; determining an aggregate memory profile, the aggregate memory profile indicating a memory unit cost for each of a plurality of memory units; determining a count of memory units to be reclaimed; identifying, based at least on the aggregate memory profile and the count of memory units to be reclaimed, a count of memory units to be reclaimed within each process instance so that a total cost is minimized to reclaim the determined count; and communicating, to each process instance having identified memory units to be reclaimed, a count of memory units to be reclaimed within the process instance.

Quorum based transactionally consistent membership management in distributed storage systems

Systems and methods that restore a failed reconfiguration of nodes in a distributed environment. By analyzing reports from read/write quorums of nodes associated with a configuration, automatic recovery for data partitions can be facilitated. Moreover, a configuration manager component tracks current configurations for replication units and determines whether a reconfiguration is required (e.g., due to node failures, node recovery, replica additions/deletions, replica moves, or replica role changes, and the like.) Reconfigurations of data activated as being replicated from an old configuration to being replicated on a new configuration may be performed in a transactionally consistent manner based on dynamic quorums associated with the new configuration and the old configuration.

Quorum based transactionally consistent membership management in distributed storage systems

Systems and methods that restore a failed reconfiguration of nodes in a distributed environment. By analyzing reports from read/write quorums of nodes associated with a configuration, automatic recovery for data partitions can be facilitated. Moreover, a configuration manager component tracks current configurations for replication units and determines whether a reconfiguration is required (e.g., due to node failures, node recovery, replica additions/deletions, replica moves, or replica role changes, and the like.) Reconfigurations of data activated as being replicated from an old configuration to being replicated on a new configuration may be performed in a transactionally consistent manner based on dynamic quorums associated with the new configuration and the old configuration.

Quorum based transactionally consistent membership management in distributed storage systems

Systems and methods for a large object infrastructure in a database system

Various embodiments of the present invention are direct to the utilization of Blob Handles (BHs) (item 300) which are an internal representation of a large value. BHs are immutable and stateless.references to a large data object. The structure of a BH (item 300) contains enough information to return an ILockBytes interface in order to provide access to the corresponding large data block, and a BH can also return information regarding its own lifetime description. A BH can be completely described using (a) a pointer to the beginning of BH data and (b) the byte-length of the BH.

Systems and methods for a large object infrastructure in a database system

Various embodiments of the present invention are direct to the utilization of Blob Handles (BHs) (item 300) which are an internal representation of a large value. BHs are immutable and stateless.references to a large data object. The structure of a BH (item 300) contains enough information to return an ILockBytes interface in order to provide access to the corresponding large data block, and a BH can also return information regarding its own lifetime description. A BH can be completely described using (a) a pointer to the beginning of BH data and (b) the byte-length of the BH.

Exposing control to enable interactive schedulers for cloud cluster orchestration systems

Methods, systems, and computer program products are provided for a compute cluster comprising placement and load balancing (PLB) logic that receives data (e.g., state metadata) relating to a service (e.g., database service) executing on the compute cluster, from a resource manager executing on the compute cluster, via a first API associated with the resource manager. The PLB logic receives second data from the service via a second API and determines whether a PLB action is indicated based on one of the second data or a combination of the first data and the second data. When a PLB action is indicated, the PLB logic sends a command to the resource manager to execute the PLB action. The PLB logic also receives queries from clients external to the compute cluster and may spawn a child PLB logic to offload PLB operations, respond to queries, or perform software validation in the child.

Differential overbooking in a cloud computing environment

Techniques for differential overbooking on a cloud database. These techniques may include determining a reservation amount of a multi-tenant resource for a first service of a based upon an overbooking characteristic of the first service, and determining that a total usage value of the multi-tenant resource by a plurality of services is greater than a threshold value. In addition, the techniques may include determining a service usage value of the multi-tenant resource by the first service, determining a first overage value of the first service based on the service usage value and the reservation amount, and performing a resource reclamation process over the multi-tenant resource based on the first overage value of the first service.

Differential overbooking in a cloud computing environment

Techniques for differential overbooking on a cloud database. These techniques may include determining a reservation amount of a multi-tenant resource for a first service of a based upon an overbooking characteristic of the first service, and determining that a total usage value of the multi-tenant resource by a plurality of services is greater than a threshold value. In addition, the techniques may include determining a service usage value of the multi-tenant resource by the first service, determining a first overage value of the first service based on the service usage value and the reservation amount, and performing a resource reclamation process over the multi-tenant resource based on the first overage value of the first service.