Abstract: System, method, and various embodiments for providing a data access and recommendation system are described herein. An embodiment operates by identifying a column access of one or more data values of a first column of a plurality of columns of a table of a database during a sampling period. A count of how many of the one or more data values are accessed during the column access are recorded. A first counter is incremented by the count. The sampling period is determined to have expired. A load recommendation on how to load data values into the first column based on the first counter is computed. The load recommendation for implementation into the database for one or more subsequent column accesses is provided.

Abstract: A system and method, including determining, by a processor, a data type for each column of a database table; determining, by the processor and based on the determined data type for each column of the database table, an indication of a size of the database table; calculating, by the processor and based on the determined indication of the size of the database table, a start nbit size for a nbit compression process to be used on the database table; specifying, by the processor, the calculated start nbit size for the nbit compression process; and compressing the database table by executing the nbit data compression process using the specified start nbit size.

Abstract: System, method, and various embodiments for providing a data access and recommendation system are described herein. An embodiment operates by identifying a column access of one or more data values of a first column of a plurality of columns of a table of a database during a sampling period. A count of how many of the one or more data values are accessed during the column access are recorded. A first counter is incremented by the count. The sampling period is determined to have expired. A load recommendation on how to load data values into the first column based on the first counter is computed. The load recommendation for implementation into the database for one or more subsequent column accesses is provided.

Abstract: System, method, and various embodiments for providing a data access and recommendation system are described herein. An embodiment operates by identifying a column access of one or more data values of a first column of a plurality of columns of a table of a database during a sampling period. A count of how many of the one or more data values are accessed during the column access are recorded. A first counter, corresponding to the first column and stored in a distributed hash table, is incremented by the count. The sampling period is determined to have expired. A load recommendation on how to load data values into the first column based on the first counter is computed. The load recommendation for implementation into the database for one or more subsequent column accesses is provided.

Abstract: Disclosed herein are systems, methods, and devices for providing load unit recommendations. An example method includes monitoring queries executed by a database management system including a database object, determining an access frequency of the database object based upon the monitoring, and determining relative access counter information for the database object based on the access frequency. Subsequently, the method includes generating a sorted element based on the relative access counter information, determining threshold values based on threshold information and the sorted element, and determining a load unit for the database object based on the sorted element and the threshold values. The load unit indicates whether to load the whole database object, or only a portion thereof, into a main memory of the DBMS while accessing the database object.

Abstract: System, method, and various embodiments for providing a data access and recommendation system are described herein. An embodiment operates by identifying a column access of one or more data values of a first column of a plurality of columns of a table of a database during a sampling period. A count of how many of the one or more data values are accessed during the column access are recorded. A first counter, corresponding to the first column and stored in a distributed hash table, is incremented by the count. The sampling period is determined to have expired. A load recommendation on how to load data values into the first column based on the first counter is computed. The load recommendation for implementation into the database for one or more subsequent column accesses is provided.

Abstract: The subject matter disclosed herein relates to out of memory error handling in a database system. A database operation can be received by an in-memory database. The database operation can be for a database object stored in a database table that can be represented as a plurality of pages that can be persisted in a page chain. The in-memory database can reserve out of memory space sufficient to load a predetermined number of pages in the page chain into memory. The in-memory database can iteratively process each page in the page chain until completion of the database operation. The iterative process can include loading the page from persistence into memory of the in-memory database, performing at least a portion of the database operation using the loaded page, and unloading the page from the memory of the in-memory database. Related apparatus, systems, techniques, and articles are also described.

Abstract: Disclosed herein are system, method, and device embodiments for providing load unit recommendations. An embodiment operates by monitoring queries executed by a database management system including a database object, determining an access frequency of the database object based upon the monitoring, and determining relative access counter information for the database object based on the access frequency. Some embodiments may further operate by generating a sorted element based on the relative access counter information, determining threshold values based on threshold information and the sorted element, and determining a load unit for the database object based on the sorted element and the threshold values, wherein the load unit may indicate whether to load the whole database object into main memory of the DBMS while accessing the database object or only load a portion of the database object into main memory of the DBMS when accessing the database object.

Abstract: Disclosed herein are system, method, and computer program product embodiments for altering the data type of a column in a database. An embodiment operates by converting an original dictionary associated with a column into a new dictionary. The new dictionary stores the values of the original dictionary using a different data type. An index vector containing the keys of the original dictionary is then updated to contain the associated keys of the new dictionary. Because the size of the original dictionary is often substantially smaller than the number of rows in the associated column, this dictionary conversion decreases the computation cost to the database system of altering the data type of the column and reduces or even minimizes database downtime for users.

Abstract: A system and method, including determining, by a processor, a data type for each column of a database table; determining, by the processor and based on the determined data type for each column of the database table, an indication of a size of the database table; calculating, by the processor and based on the determined indication of the size of the database table, a start nbit size for a nbit compression process to be used on the database table; specifying, by the processor, the calculated start nbit size for the nbit compression process; and compressing the database table by executing the nbit data compression process using the specified start nbit size.

Abstract: A system and method, including determining, by a processor, a data type for each column of a database table; determining, by the processor and based on the determined data type for each column of the database table, an indication of a size of the database table; calculating, by the processor and based on the determined indication of the size of the database table, a start nbit size for a nbit compression process to be used on the database table; specifying, by the processor, the calculated start nbit size for the nbit compression process; and compressing the database table by executing the nbit data compression process using the specified start nbit size.

Abstract: A system and method, including determining, by a processor, a data type for each column of a database table; determining, by the processor and based on the determined data type for each column of the database table, an indication of a size of the database table; calculating, by the processor and based on the determined indication of the size of the database table, a start nbit size for a nbit compression process to be used on the database table; specifying, by the processor, the calculated start nbit size for the nbit compression process; and compressing the database table by executing the nbit data compression process using the specified start nbit size.

Abstract: Log records are accessed as part of a database operation in a database. The log records log insert, update, and delete operations in the database and include, for each row, a row position, a fragment identifier (ID), and a row ID. Thereafter, as part of the database operation, rows specified by the log records are located by: using the fragment identifier and the row position within the corresponding record of the log if the fragment with the corresponding fragment identifier is still available, otherwise, using the row identifier within the corresponding record of the log to look up the row position in an index of a corresponding row identifier column. The database operation is then finalized using the located rows. Related apparatus, systems, techniques and articles are also described.

Abstract: The subject matter disclosed herein relates to out of memory error handling in a database system. A database operation can be received by an in-memory database. The database operation can be for a database object stored in a database table that can be represented as a plurality of pages that can be persisted in a page chain. The in-memory database can reserve out of memory space sufficient to load a predetermined number of pages in the page chain into memory. The in-memory database can iteratively process each page in the page chain until completion of the database operation. The iterative process can include loading the page from persistence into memory of the in-memory database, performing at least a portion of the database operation using the loaded page, and unloading the page from the memory of the in-memory database. Related apparatus, systems, techniques, and articles are also described.

Abstract: Log records are accessed as part of a database operation in a database. The log records log insert, update, and delete operations in the database and include, for each row, a row position, a fragment identifier (ID), and a row ID. Thereafter, as part of the database operation, rows specified by the log records are located by: using the fragment identifier and the row position within the corresponding record of the log if the fragment with the corresponding fragment identifier is still available, otherwise, using the row identifier within the corresponding record of the log to look up the row position in an index of a corresponding row identifier column. The database operation is then finalized using the located rows. Related apparatus, systems, techniques and articles are also described.

Abstract: Disclosed herein are system, method, and computer program product embodiments for altering the data type of a column in a database. An embodiment operates by converting an original dictionary associated with a column into a new dictionary. The new dictionary stores the values of the original dictionary using a different data type. An index vector containing the keys of the original dictionary is then updated to contain the associated keys of the new dictionary. Because the size of the original dictionary is often substantially smaller than the number of rows in the associated column, this dictionary conversion decreases the computation cost to the database system of altering the data type of the column and reduces or even minimizes database downtime for users.

Abstract: Methods, systems, and computer program products are provided to manage a database system. The method includes locking during a database system idle time access by the database system to a data page of a data allocation unit, compressing during the database system idle time a data stored in the locked data page, and recording during the database system idle time an indication that the compressed and locked data page includes free storage space, wherein unlocked data pages of the data allocation unit are accessible by the database system during the compressing of the data stored in the locked data page. Thus, the data page may be compressed during idle time and the space freed therein may be used during a subsequent run time without the need for a reorganization of the data pages within the corresponding table (as in, for example, operation of a reorg+rebuild SQL command combination).

Abstract: Methods, systems, and computer program products are provided to manage a database system. The method includes locking during a database system idle time access by the database system to a data page of a data allocation unit, compressing during the database system idle time a data stored in the locked data page, and recording during the database system idle time an indication that the compressed and locked data page includes free storage space, wherein unlocked data pages of the data allocation unit are accessible by the database system during the compressing of the data stored in the locked data page. Thus, the data page may be compressed during idle time and the space freed therein may be used during a subsequent run time without the need for a reorganization of the data pages within the corresponding table (as in, for example, operation of a reorg+rebuild SQL command combination).

Abstract: Methods, systems, and computer program products are provided to efficiently allocate extremely large storage spaces for use by dynamic hash tables. A contiguous storage space is designated from which dynamic hash tables can be created. These dynamic hash tables benefit from rapid allocation by being able to reserve many allocation units (each potentially comprising a large number of pages, e.g., 256 pages) within a short span of time, rather than resorting to reserving individual pages. The efficiency from allocation and the contiguous space significantly improves performance for databases in the 50 GB-100 GB size range.

Abstract: Aspects for achieving efficient data access to data elements in a relational database management system are provided. In a computer-implemented method aspect, the efficient data access occurs by establishing a hash table for data elements of a database in a predetermined continuous space of allocated storage, and optimizing utilization of the hash table during database query operations through linear hashing, wherein extension of the hash table occurs automatically to increase a number of pages in the hash table without discernible interruptions of data access to the data elements.