Oracle International Corporation

Tolga Yurek

Wilson Wai Shun Chan

Angelo Pruscino

Yunrui Li

Tak Fung Wang

Eugene Reddy Ho

Michael Zoll

Wilson Wai Chan

Stefan Heinrich Roesch

John C Hsu

Anjan Kumar Amirishetty

Deepti Srivastava

Sashikanth Chandrasekaran

Mahesh Baburao Girkar

Vinay H Srihari

Neil MacNaughton

Chi Cao Minh

Yu Kin Ho

Shanshan Song

Chen Yang

Ping-Hsiu Hsieh

Beverly Zane

Techniques related to instance recovery using Bloom filters are disclosed. A multi-node node database management system (DBMS) includes a first database server instance and a second database server instance. A recovery set includes a set of data blocks that have been modified by a first database server instance and not persisted. A Bloom filter is generated to indicate whether data blocks are excluded from the recovery set. The Bloom filter is sent to the second database server instance, which determines whether the Bloom filter indicates that a particular data block is excluded from the recovery set. Based on determining that the Bloom filter indicates that the particular data block is excluded from the recovery set, access to the particular data block is granted.

Instance recovery using bloom filters

Techniques are described herein for quick identification of a set of units of data for which recovery operations are to be performed to redo or undo changes made by the failed node. When a lock is requested by an instance, lock information for the lock request is replicated by another instance. If the instance fails, the other instance may use the replicated lock information to determine a set of data blocks for recovery operations. The set of data blocks is available in memory of a recovery instance when a given node fails, and does not have to be completely generated by scanning a redo log.

Technique for higher availability in a multi-node system using replicated lock information to determine a set of data blocks for recovery

According to embodiments, reconfiguration of lock masters for a cluster of nodes is optimized using coordinated hash indexes to index into the master hash table and into local hash tables stored on the nodes of the cluster. A DBMS uses a hybrid hash index, a portion of which represents a corresponding master hash index, to index into both the master hash table and into a local hash table for a given lock. The hash index used to store lock metadata in a particular local hash table bucket, on a particular node, encodes the lock master index, for a master hash table, to which the locks in the local hash table bucket correspond. Only the portions of the local hash table on the lock master that correspond to the index of the master hash table bucket need to be scanned in order to perform needed tasks for lock master reconfiguration.

Coordinated hash table indexes to facilitate reducing database reconfiguration time

Embodiment provide that each pluggable database (PDB) in a container database is associated with a distinct distributed lock manager (DLM) domain. Thus, in order to access a PDB, a database server instance joins the DLM domain for the PDB. To perform actions on the PDB, the instance secures locks that belong to the DLM domain for the particular PDB. As such, buffers storing data for the PDB may be managed separately from buffers storing data for other PDBs using the PDB-specific DLM domains. An instance forcefully closing a particular PDB marks the DLM domain of the PDB as invalid, which allows detection of the forceful closure by a recovery instance. Detection of an invalid DLM domain by an instance causes the instance to automatically recover the PDB by accessing pertinent ranges of redo logs and replaying changes made to data blocks for the PDB indicated in the logs.

Forceful closure and automatic recovery of pluggable databases in a shared-everything cluster multitenant container database

Techniques for taking one or more nodes of a multi-node database system offline are provided. Initially, the multi-node database system uses a first data access management system (e.g., a distributed lock management system) to manage access to data stored in a database. In response to determining that one or more nodes need to be taken offline or otherwise become unavailable, the remaining nodes implement a second data access management system (e.g., an affinity-based access system) to manage access to data stored in the database. After the offline nodes are brought back online, all the nodes in the multi-node database system implement the first data access management system again. The transitions between the two data access management system may involve multiple phases that involve communicating different types of information between nodes that are taken offline and nodes that are not taken offline.

Planned cluster node maintenance with low impact on application throughput

Techniques for adaptive trace logging include, in one embodiment, obtaining input data on trace logging behavior and computing resources used by trace logging. Based on the obtained input data, an adaptive trace logging module automatically takes action at runtime to reduce the amount of computing resources consumed by tracing logging. For example, the action taken may include decreasing a trace logging level of an executing software program to reduce the number of trace logging messages added to a trace log. In another embodiment, the techniques include detecting a condition of an executing software program that warrants a change to a trace logging level of the executing program. The adaptive trace logging module automatically changes the trace logging level of the executing program as-needed for the detected condition. For example, the adaptive trace logging module may increase the trace logging level of an executing program upon detecting a deadlock or other abnormal condition of the executing program. By automatically increasing the trace logging level upon detecting an abnormal condition, additional trace logging messages may be written to a trace log aiding diagnosis and troubleshooting of the condition.

Techniques for adaptive trace logging

A method, system, and computer program product. The method for non-intrusive redeployment of a standby database facility comprises configuring a database system having a shared lock manager process to synchronize two or more concurrent access instances, then granting lock requests for access to a cache of database blocks. At some moment in time, the shared lock manager process may fail, and a monitor process detects the failure or other stoppage of the shared lock manager process. A new shared lock manager process and other processes are started, at least one of which serves for identifying the database blocks in the cache that have not yet been written to the database. The identified blocks are formed into a recovery set of redo operations. During this time, incoming requests for access to the cache of database blocks are briefly blocked, at least until the recovery set of redo operations has been formed.

Automatic recovery of a failed standby database in a cluster

Described herein are techniques for adaptively managing timers that are used in various layers of a node. In many cases, the number of timers that occur in the system is reduced by proactively and reactively adjusting values of the timers based on conditions affecting the system, thereby making such a system to perform significantly better and more resiliently than otherwise.

Adaptive cluster timer manager

A method and apparatus for managing locks in a database system is provided. A master node grants a lock on a first resource and a group of resources that includes the first resource to a first requester node. The requester node receives a mapping corresponding to the group of resources that may indicate that a lock already exists for a second resource in the group. If the requester node desires a lock on a resource located in the group, the requester node grants itself the lock without notifying the master node. A second requester node requests a lock for a particular resource in the group of resources. The first requester node grants the lock on the particular resource and updates the mapping to indicate that a different node holds a lock for the particular resource.

Adaptive region locking

Techniques are provided for responding to the termination of a node by selecting another node, and assigning to the selected node the affinity relationships that existed between the terminated node and one or more objects. The resources that belong to the objects involved in the affinity relationships are remastered to the selected node. The selected node then performs recovery of the resources that had been opened by the terminated node and/or serves as a failover node to execute the transactions that had been executing on the terminated node.

Affinity-based recovery/failover in a cluster environment

In a multi-node database system, a list of data blocks to perform recovery operations on in the event of failure of a given node is dynamically maintained on another node. List is available when the given node fails, and allows the database to be made available more quickly.

I/O free recovery set determination

Techniques are provided for responding to the termination of a node executing one or more transactions by selecting another node to complete the transactions, and assigning to the selected node the affinity relationships that existed between the terminated node and the objects being accessed by said transactions.

Optimization for transaction failover in a multi-node system environment where objects' mastership is based on access patterns

Remastering of shared resources among nodes in a cluster, while minimizing the time that such resources are unavailable for access, comprises dividing the shared resources being remastered into multiple 'windows' and freezing and remastering one window at a time. The remastering windows are defined over one or more buckets associated with a hash table of resources. In clusters with unequally sized hash tables, an enhancement to the fundamental windowing approach utilizes a functionally specific hashing algorithm and a hash table size constraint to ensure that the set of all resources that hash to a given bucket in a hash table of a given size will hash precisely to the same bucket, plus a set of higher buckets which are well defined, in a node that has a larger hash table.

Techniques for multiple window resource remastering among nodes of a cluster

Techniques are described herein for handling lock-related inconsistencies. As mentioned above, such inconsistencies occur when two or more sets of lock information, relating to the same resource, convey inconsistent information about locks requested and/or granted on that resource. In general, the techniques involve causing the locally-stored lock information about a resource to be sent to the master node of the resource. The master node of the resource compares the lock information thus received against the lock information maintained by the master node. Based on the comparison, the master node determines how to resolve the lock-related inconsistency, and sends messages to those nodes that need to change their local lock information for the resource. Once all of the lock information has been made consistent, the resource made available for access.

Techniques for handling lock-related inconsistencies

Techniques are described for remastering shared resources among nodes in a cluster, while minimizing the number of resources that are unavailable for access ('frozen') during the remastering operation. Only the resources that are being remastered from one node to one or more other nodes are frozen, whereas the other resources that are not being remastered are not frozen and are, therefore, still accessible. For example, in the context of a database cluster, there is no longer a need to freeze the entire database during a reconfiguration remastering operation. Consequently, during the remastering operation requests for access to the resources that are not being remastered can be processed and locks granted thereon.

Growing community of inventors

Foster City, CA, United States of America

Tolga Yurek