Abstract:
An approach for implementing function semantic based partition-wise SQL execution and partition pruning in a data processing system is provided. The system receives a query directed to a range-partitioned table and determines if operation key(s) of the query include function(s) over the table partitioning key(s). If so, the system obtains a set of values corresponding to each partition by evaluating the function(s) on a low bound and/or a high bound table partitioning key value corresponding to the partition. The system may then compare the sets of values corresponding to different partitions and determine whether to aggregate results obtained by executing the query over the partitions based on the comparison. The system may also determine whether to prune any partitions from processing based on a set of correlations between the set of values for each partition and predicate(s) of the query including function(s) over the table partitioning key(s).
Abstract:
An approach for implementing function semantic based partition-wise SQL execution and partition pruning in a data processing system is provided. The system receives a query directed to a range-partitioned table and determines if operation key(s) of the query include function(s) over the table partitioning key(s). If so, the system obtains a set of values corresponding to each partition by evaluating the function(s) on a low bound and/or a high bound table partitioning key value corresponding to the partition. The system may then compare the sets of values corresponding to different partitions and determine whether to aggregate results obtained by executing the query over the partitions based on the comparison. The system may also determine whether to prune any partitions from processing based on a set of correlations between the set of values for each partition and predicate(s) of the query including function(s) over the table partitioning key(s).
Abstract:
Techniques are described for maintaining coherency of a portion of a database object populated in the volatile memories of multiple nodes in a database cluster. The techniques involve maintaining a local invalidation bitmap for chunks of data stored in memory in each particular node in the cluster by tracking locks granted by a lock manager. During a pre-loading operation, each given node requests a set of shared locks associated with the chunks of data to be store in the given node's memory. When a request to release one of these shared locks occurs, the in-memory copy of those data items may be invalidated in the node releasing its shared lock.
Abstract:
Techniques are herein described for loading a portion of a database object into volatile memory without blocking database manipulation language transactions. The techniques involve invalidating data items loaded from blocks affected by a transaction, referred to as a straddling transaction that started before the load time and committed after the load time. Identifying these straddling transactions involves reviewing one or more transaction lists associated with the set of data items loaded in memory. The transaction list may be read in reverse temporal order of commit to identify a transaction meeting the criteria of starting before the load start, not committing before the load time, and affecting a data item loaded in memory.
Abstract:
Techniques are provided for maintaining data persistently in one format, but making that data available to a database server in more than one format. For example, one of the formats in which the data is made available for query processing is based on the on-disk format, while another of the formats in which the data is made available for query processing is independent of the on-disk format. Data that is in the format that is independent of the disk format may be maintained exclusively in volatile memory to reduce the overhead associated with keeping the data in sync with the on-disk format copies of the data.
Abstract:
Techniques are provided for maintaining data persistently in one format, but making that data available to a database server in more than one format. For example, one of the formats in which the data is made available for query processing is based on the on-disk format, while another of the formats in which the data is made available for query processing is independent of the on-disk format. Data that is in the format that is independent of the disk format may be maintained exclusively in volatile memory to reduce the overhead associated with keeping the data in sync with the on-disk format copies of the data.
Abstract:
Techniques are herein described for loading a portion of a database object into volatile memory without blocking database manipulation language transactions. The techniques involve invalidating data items loaded from blocks affected by a transaction, referred to as a straddling transaction that started before the load time and committed after the load time. Identifying these straddling transactions involves reviewing one or more transaction lists associated with the set of data items loaded in memory. The transaction list may be read in reverse temporal order of commit to identify a transaction meeting the criteria of starting before the load start, not committing before the load time, and affecting a data item loaded in memory.
Abstract:
To prioritize repopulation of in-memory compression units (IMCU), a database server compresses, into an IMCU, a plurality of data units from a database table. In response to changes to any of the plurality of data units within the database table, the database server performs the steps of: (a) invalidating corresponding data units in the IMCU; (b) incrementing an invalidity counter of the IMCU that reflects how many data units within the IMCU have been invalidated; (c) receiving a data request that targets one or more of the plurality of data units of the database table; (d) in response to receiving the data request, incrementing an access counter of the IMCU; and (e) determining a priority for repopulating the IMCU based, at least in part, on the invalidity counter and the access counter.
Abstract:
Techniques for non-disruptive versioning of in-memory units in a database are provided. A database server generates and maintains a first IMU that reflects changes made to a mirrored-data-set up to a first snapshot time, and a second IMU that reflects changes made to the mirrored-data-set up to a second snapshot time. During a first period, the database server responds to updates to first data items in the mirrored data by storing first staleness metadata that indicates that the copies of the first data items in the first IMU are stale. During a second period, the database server responds to updates to second data items in the mirrored data by storing second staleness metadata that indicates that the copies of the second data items in the second IMU are stale. The database server responds to a request by accessing the first IMU or the second IMU.
Abstract:
Techniques are provided for maintaining data persistently in one format, but making that data available to a database server in more than one format. For example, one of the formats in which the data is made available for query processing is based on the on-disk format, while another of the formats in which the data is made available for query processing is independent of the on-disk format. Data that is in the format that is independent of the disk format may be maintained exclusively in volatile memory to reduce the overhead associated with keeping the data in sync with the on-disk format copies of the data.