Abstract: A database system determines execution plans for database queries by evaluating a number of partial solutions for each database query. The database system determines a partial solutions limit on the number of partial solutions to be evaluated for determining the execution plan of the query. The database system determines a plurality of partial solutions, each partial solution corresponding to a portion of the execution plan for processing the database query. The database system evaluates a number of candidate partial solutions for determining a partial solution. The number of candidate partial solutions evaluated is determined based on the partial solutions limit. The database system combines the plurality of partial solutions to obtain an execution plan for the database query. The database system executes the database query by executing the execution plan.

Abstract: A database system rewrites database queries based on rewrite constraints specification. The rewrite constraints specification provides directives to the database system to generate temporary tables for storing intermediate results of database queries and rewrite the corresponding database queries in terms of the temporary tables. The subqueries for matching the rewrite constraints specification may be specified in various ways. For example, the rewrite constraints specification may identify the subqueries by using one or more aliases. The rewrite constraints specification may specify a list of tables such that all database queries that join the database tables specified in the rewrite constraints specification are determined to match. The optimizer is able to optimize the rewritten database queries better by getting a better estimate for the statistics describing the temporary tables.

Abstract: A database system allows users to specify plan constraint specification that limit choices of execution plans considered by an optimizer of the database system for optimizing database queries. The plan constraint specification specifies attributes of execution plans. The plan constraint specification may identify tables/intermediate results that the plan constraint is applicable to using table names or aliases. The database system applies the plan constraint specification to database queries that match the tables/aliases specified in the plan constraint specification. The database system limits the choice of execution plans evaluated for a database query to execution plans satisfying the attributes specified in an applicable plan constraint specification. The plan constraint specification may specify distribution of a table, a join order for tables, the join mechanism, cardinality of a table or intermediate result, and so on.

Abstract: A logical backup of a database is performed that allows physical properties of the database to be preserved upon restore. The physical properties of the database include properties related to storage of the data on the hard disk. Preserving the physical properties of a database allows performance debugging of the source database by performing performance tests on the target database rather than a production system. Incremental backup of metadata of a database is performed to minimize execution of statements that provide the final configuration of the database. Incremental backup is performed by restoring a database using a full backup and applying incremental backups to reach a particular state. The user can inspect the restored database after applying each incremental backup to determine whether the database has reached a desired state.

Abstract: A database system performs hash join process for processing queries that join an inner and an outer database table. The hash join processes builds a hash table in memory for the inner table. The database system receives a limit on the memory for storing the hash table. The database system maximizes the number of partitions stored in memory for the hash table. If the hash table exceeds the limit of the memory while adding rows from the inner table, the database system selects a partition for spilling to a persistent storage. The partition selected for spilling to may be the largest partition or a partition larger than most of the partitions. The database system initializes the hash table to a number of partitions that is substantially equal to half of the total number of blocks that can be stored within the specified limit of memory for the hash table.

Abstract: A database system maintains table data in sorted order. The table data becomes unsorted over time due to add, delete, and update operations. These operations are performed such that the table comprises an initial sorted region followed by an unsorted region. The database system performs an incremental operation to rewrite the table in sorted order. The database system partitions the unsorted region into a plurality of partitions comprising sorted rows within each partition. The database system iteratively merges rows from the partitions to the sorted region of the table. The database system selects a set of lowest tanked rows from the partitions. The database system merges these lowest ranked rows with the sorted region while maintaining the sort order of the sorted region. The database system repeats these steps until all the partitions are processed. The database may store data in columnar fashion.

Abstract: Data of a columnar database is organized into extents. Each extent occupies contiguous storage on the disk. An extent stores database blocks of a column of a database table. The database system adds new database blocks of a column to the extents assigned to that column. When a request for adding a block to a table is received, the extent for the table and column combination is obtained and the block added to the extent. Prefetching strategies are used to retrieve database blocks in advance of an actual request. The rate of prefetching is determined per column. The rate of prefetching is adjusted based on the number of faults encountered for the column. Database blocks no longer needed in memory are pushed out. When a scan process is reading blocks, as soon as the block has been processed it is scheduled to be pushed out.

Abstract: Scalable means are provided for diagnosing the health of a parallel system comprising multiple nodes interconnected using one or more switching networks. The node pings other nodes via different paths at regular intervals. If more than a threshold number of pings are missed from a node, the system performs fault detection by entering a freeze state in which nodes do not send or receive any messages except ping messages. If ping messages still fail to reach destination nodes, the parallel system identifies faulty components that are causing ping messages to fail. Once the faulty component is identified, the parallel system is unfrozen by allowing nodes to communicate all messages. If redundant computers and/or switches are present, the parallel system is automatically reconfigured to avoid the faulty components.

Abstract: A database system optimizes database queries that comprise subqueries. The database system factors out computation from two or more subqueries to a reusable subquery. The reusable subquery returns a result set. The subqueries are rewritten to use the result set and the database query modified to use the rewritten subqueries. The modified database query performs efficiently since the result set is computed only once for each subquery that uses the reusable query. The database system also composes nested subqueries that compute aggregate values. The database system identifies an inner subquery nested within an outer subquery, each subquery computing an aggregate value. The database system determines a new aggregate function corresponding to a composition of aggregate functions of the inner and the outer queries. The database system determines a composed query using the inner query with the outer query. The composed query uses the new aggregate function.

Abstract: Data of a columnar database is organized into extents. Each extent occupies contiguous storage on the disk. An extent stores database blocks of a column of a database table. The database system adds new database blocks of a column to the extents assigned to that column. When a request for adding a block to a table is received, the extent for the table and column combination is obtained and the block added to the extent. Prefetching strategies are used to retrieve database blocks in advance of an actual request. The rate of prefetching is determined per column. The rate of prefetching is adjusted based on the number of faults encountered for the column. Database blocks no longer needed in memory are pushed out. When a scan process is reading blocks, as soon as the block has been processed it is scheduled to be pushed out.

Abstract: Data of a columnar database is organized into extents. Each extent occupies contiguous storage on the disk. An extent stores database blocks of a column of a database table. The database system adds new database blocks of a column to the extents assigned to that column. When a request for adding a block to a table is received, the extent for the table and column combination is obtained and the block added to the extent. Prefetching strategies are used to retrieve database blocks in advance of an actual request. The rate of prefetching is determined per column. The rate of prefetching is adjusted based on the number of faults encountered for the column. Database blocks no longer needed in memory are pushed out. When a scan process is reading blocks, as soon as the block has been processed it is scheduled to be pushed out.

Abstract: A system and method for enhancing data throughput in data warehousing environments by connecting multiple servers having local storages with designated external storage systems, such as, for example, those provided by SANS. The system and method may preserve a full reference copy of the data in a protected environment (e.g., on the external storage system) that is fully available. The system and method may enhance overall I/O potential performance and reliability for efficient and reliable system resource utilization.

Abstract: The same data is stored in at least two different database management systems (DBMS's), including a columnar DBMS (320.2) and a non-columnar (e.g. row-oriented) DBMS (320.1). The columnar DBMS may provide fast responses to queries involving aggregation, and such queries can be routed to the columnar DBMS. A query may be routed to the non-columnar DBMS if for example the query execution involves only small DBMS tables on the non-columnar DBMS. In some situations, an execution time estimate can be obtained from each DBMS, and the query is routed to the DBMS providing the shortest estimate.

Abstract: A system and method for enhancing data throughput in data warehousing environments by connecting multiple servers having local storages with designated external storage systems, such as, for example, those provided by SANs. The system and method may preserve a full reference copy of the data in a protected environment (e.g., on the external storage system) that is fully available. The system and method may enhance overall I/O potential performance and reliability for efficient and reliable system resource utilization.