Abstract: Techniques for optimizing a query with an extrema function are provided. In main memory, a data summary is maintained for a plurality of extents stored by at least one storage server. The data summary includes an extent minimum value and an extent maximum value for one or more columns. A storage server request is received, from a database server, based on a query with an extrema function applied to a particular column of a particular table. The data summaries for a set of relevant extents are processed by maintaining at least one global extrema value corresponding to the extrema function and, for each relevant extent of the set of relevant extents, determining whether to scan records of the relevant extent based on at least one of the global extrema value and an extent summary value of the data summary of the relevant extent.

Abstract: A method and computer program product for an abstract syntax tree (AST) builder for faster Earley parser. The algorithm for building an AST based on an amplified LRE (Left Recursive Earley parser) technique is provided. The proposed method constructs the AST during the recognition process. The proposed method preserves enough structural information during recognition phase that allows to avoid a mapping step and to eliminate the converter module. The LRE method is used in such a way that the AST processor can produce its output working directly with LRE data structures. This important feature leads to essential performance improvement of the entire parsing process.

Abstract: Processing resources at a storage system for a database server are utilized to perform aspects of a join operation that would conventionally be performed by the database server. When requesting a range of data units from a storage system, the database server includes join metadata describing aspects of the join operation for which the data is being requested. The join metadata may be, for instance, a bloom filter. The storage system reads the requested data from disk as normal. However, prior to sending the requested data back to the storage system, the storage system analyzes the raw data based on the join metadata, removing a certain amount of data that is guaranteed to be irrelevant to the join operation. The storage system then returns filtered data to the database server. The database system thereby avoids the unnecessary transfer of certain data between the storage system and the database server.

Abstract: Techniques for optimizing a query with an extrema function are provided. In main memory, a data summary is maintained for a plurality of extents stored by at least one storage server. The data summary includes an extent minimum value and an extent maximum value for one or more columns. A storage server request is received, from a database server, based on a query with an extrema function applied to a particular column of a particular table. The data summaries for a set of relevant extents are processed by maintaining at least one global extrema value corresponding to the extrema function and, for each relevant extent of the set of relevant extents, determining whether to scan records of the relevant extent based on at least one of the global extrema value and an extent summary value of the data summary of the relevant extent.

Abstract: Processing resources at a storage system for a database server are utilized to perform aspects of a join operation that would conventionally be performed by the database server. When requesting a range of data units from a storage system, the database server includes join metadata describing aspects of the join operation for which the data is being requested. The join metadata may be, for instance, a bloom filter. The storage system reads the requested data from disk as normal. However, prior to sending the requested data back to the storage system, the storage system analyzes the raw data based on the join metadata, removing a certain amount of data that is guaranteed to be irrelevant to the join operation. The storage system then returns filtered data to the database server. The database system thereby avoids the unnecessary transfer of certain data between the storage system and the database server.

Abstract: A method, device, and computer readable medium for striping rows of data across logical units of storage with an affinity for columns is provided. Alternately, a method, device, and computer readable medium for striping columns of data across logical units of storage with an affinity for rows is provided. When data of a logical slice is requested, a mapping may provide information for determining which logical unit is likely to store the logical slice. In one embodiment, data is retrieved from logical units that are predicted to store the logical slice. In another embodiment, data is retrieved from several logical units, and the data not mapped to the logical unit is removed from the retrieved data.

Abstract: Processing resources at a storage system for a database server are utilized to perform aspects of a join operation that would conventionally be performed by the database server. When requesting a range of data units from a storage system, the database server includes join metadata describing aspects of the join operation for which the data is being requested. The join metadata may be, for instance, a bloom filter. The storage system reads the requested data from disk as normal. However, prior to sending the requested data back to the storage system, the storage system analyzes the raw data based on the join metadata, removing a certain amount of data that is guaranteed to be irrelevant to the join operation. The storage system then returns filtered data to the database server. The database system thereby avoids the unnecessary transfer of certain data between the storage system and the database server.

Abstract: A method, device, and computer readable medium for striping rows of data across logical units of storage with an affinity for columns is provided. Alternately, a method, device, and computer readable medium for striping columns of data across logical units of storage with an affinity for rows is provided. When data of a logical slice is requested, a mapping may provide information for determining which logical unit is likely to store the logical slice. In one embodiment, data is retrieved from logical units that are predicted to store the logical slice. In another embodiment, data is retrieved from several logical units, and the data not mapped to the logical unit is removed from the retrieved data.

Abstract: A method, device, and computer readable medium for striping rows of data across logical units of storage with an affinity for columns is provided. Alternately, a method, device, and computer readable medium for striping columns of data across logical units of storage with an affinity for rows is provided. When data of a logical slice is requested, a mapping may provide information for determining which logical unit is likely to store the logical slice. In one embodiment, data is retrieved from logical units that are predicted to store the logical slice. In another embodiment, data is retrieved from several logical units, and the data not mapped to the logical unit is removed from the retrieved data.

Abstract: Stored data are transported between different systems having different platforms by converting the format of the stored data into a common format either before or after transmitting the stored data from the source database system to the target database system. The common format may be a format that is universal in that the common format is not machine dependent. The stored data may be kept in the common format at the target database system and never converted to another format. Optionally, the stored data may be converted from the common format to a format associated with the target database system, thereby facilitating backward compatibility. A tool may be provided for performing the conversion.

Abstract: A method, device, and computer readable medium for striping rows of data across logical units of storage with an affinity for columns is provided. Alternately, a method, device, and computer readable medium for striping columns of data across logical units of storage with an affinity for rows is provided. When data of a logical slice is requested, a mapping may provide information for determining which logical unit is likely to store the logical slice. In one embodiment, data is retrieved from logical units that are predicted to store the logical slice. In another embodiment, data is retrieved from several logical units, and the data not mapped to the logical unit is removed from the retrieved data.

Abstract: A method, system, and computer program product for cost based analysis for data access in a database management system. In one approach, the method, system, and computer program product identifies data to access. A first cost for direct I/O storage access and a second cost for cache access are then determined for accessing the data. A comparison between the first cost and the second cost is then performed. Finally, a first portion of identified data is accessed based at least in part upon the comparison.

Abstract: A method, device, and computer readable medium for striping rows of data across logical units of storage with an affinity for columns is provided. Alternately, a method, device, and computer readable medium for striping columns of data across logical units of storage with an affinity for rows is provided. When data of a logical slice is requested, a mapping may provide information for determining which logical unit is likely to store the logical slice. In one embodiment, data is retrieved from logical units that are predicted to store the logical slice. In another embodiment, data is retrieved from several logical units, and the data not mapped to the logical unit is removed from the retrieved data.

Abstract: Processing resources at a storage system for a database server are utilized to perform aspects of a join operation that would conventionally be performed by the database server. When requesting a range of data units from a storage system, the database server includes join metadata describing aspects of the join operation for which the data is being requested. The join metadata may be, for instance, a bloom filter. The storage system reads the requested data from disk as normal. However, prior to sending the requested data back to the storage system, the storage system analyzes the raw data based on the join metadata, removing a certain amount of data that is guaranteed to be irrelevant to the join operation. The storage system then returns filtered data to the database server. The database system thereby avoids the unnecessary transfer of certain data between the storage system and the database server.

Abstract: A fact table is set up without any dimension columns. The data in the table is ordered according to an order corresponding to the ordering of the dimensions. The table is divided into segments corresponding to contiguous portions of data. The portions of the table containing non-null values for the measures are placed into the segments. The size of the segments and the location segments may be determined according to the density of discontinuities in the data. An indexed organized table is used to determine the beginning and end of each segment of the table, the locations of the discontinuities in the data, and to facilitate accessing the measures of the table.

Abstract: A method, system, and computer program product forcost based analysis for data access in a database management system. In one approach, the method, system, and computer program productperforms identifying data to access, determining a first cost for direct I/O storage access and a second cost for cache access, performing a comparison between the first cost and the second cost, and accessing a first portion of identified data based upon the comparison.

Abstract: Key conditioning involves the construction of a byte orderable array from values for a possibly multi-field key concatenated key, for comparison by a sort routine. Byte-orderable sort keys are conditioned prior to execution of a sort routine, to facilitate an accurate and/or efficient sort procedure. For example, key conditioning may be applied to values in one or more columns of a database table, where the column(s) are used as keys for sorting rows of the table. Six factors are considered in encoding the byte array, such as whether nulls compare high or low; whether a field is fixed width or variable width; whether a field is guaranteed to be not null; whether a field is ordered ascending or descending; whether a field is the last field of a multi-field sort key or the only field of a sort key; and whether a field is likely to contain a significant number of zero values.

Abstract: Stored data, such as tablespaces, are transported between different systems having different platforms by converting the format of the stored data into a common format either before or after transmitting the stored data from the source database system to the target database system. The common format may be a format that is universal in that the common format is not machine dependent. The stored data may be kept in the common format at the target database system and never converted to another format. Optionally, the stored data may be converted from the common format to a format associated with the target database system, thereby facilitating backward compatibility. A tool may be provided for performing the conversion. In an embodiment each of the target and source database systems have a copy of the tool.

Abstract: A method and apparatus for creating a target database on a target platform based on a source database on a source platform is provided. A target database is created on the target platform based on data, metadata (for example, data in the system tablespace and control files), and external objects (for example, password files and externally stored tables) comprised within the source database. Data and metadata stored in tablespaces of the source database are converted to the format compatible with the target platform. The conversion of the data and metadata may be performed either at the source database or the target database. Redo information and undo information of the source database are not copied from the source database to the target database. Certain files, e.g., a password files, and links to externally stored object may be recreated on the target database.

Abstract: A fact table is set up without any dimension columns. The data in the table is ordered according to an order corresponding to the ordering of the dimensions. The table is divided into segments corresponding to contiguous portions of data. The portions of the table containing non-null values for the measures are placed into the segments. The size of the segments and the location segments may be determined according to the density of discontinuities in the data. An indexed organized table is used to determine the beginning and end of each segment of the table, the locations of the discontinuities in the data, and to facilitate accessing the measures of the table.