Abstract: Disclosed herein are system, method, and computer program product embodiments for populating a hash index and returning a handle to the hash index. An embodiment operates by determining, by at least one processor, during query optimization that a first database query has a query execution plan comprising a sub-query which executes N times a correlated predicate having an operator being one of equal and not equal to a base column. A cost of creating and probing the hash index N times and a cost of fully scanning the base column N times are compared based on the correlated predicate. Based on the comparing, it is determined whether to create on-demand a hash index.

Abstract: A compression manager may store, within an index vector, a plurality of value identifiers (IDs), each value ID representing a value within a database. A page generator may designate a number of the value IDs as defining a page within the index vector, so that the index vector includes a plurality of pages, each page including the number of value IDs. The page generator may store the index vector in a secondary memory of a main memory database. An iterator may access a requested value ID, and a page loader may load a corresponding page of the index vector that contains the requested value ID into the main memory database.

Abstract: System and methodology for automatic tuning of database query optimizer is described.

Abstract: A set-oriented locking based on in-memory bitmap for a column store database is described. An example method includes establishing a column-based in-memory database including a main store and a delta store, where the delta store has a plurality of row-visibility lock bitmaps visible to transactions at various points in time. The lock bitmaps represent a bit encoding to indicate whether there are granted row locks tables in the database. A delete or an update statement is executed with a transaction on a table. A set of row locks on rows of the table manipulated by the delete or the update statement are requested to preclude other transactions from currently deleting or updating the same rows. Accordingly, set operations are performed on the lock bitmap to manage the set of row locks associated with the transaction.

Abstract: A locking mechanism in a delta-store-based database to support long running transactions across multiple RID spaces is described. An example method includes establishing a column-based in-memory database including a main store and a delta store. A delete or an update statement is executed with a transaction on a table having plurality of table versions. The table versions are represented by bitmaps in the delta store and the bitmaps and table fragments corresponding to the table versions implement RID spaces for the table. A lock on a row of the table manipulated by the delete or the update statement is requested to preclude other transaction from deleting or updating an obsolete version of data. Upon a successful validation that the row to be locked is not the obsolete version in the RID spaces of the table, a lock is granted to the transaction.

Abstract: A delta store giving row-level versioning semantics to a non-row-level versioning underlying store is described. An example method includes establishing a column-based in-memory database including a main store and a delta store, where the main store allows only non-concurrent transactions on a same table and the delta store has a plurality of row-visibility bitmaps implementing a row-level versioning mechanism that allows concurrent transactions on the same table. A local RID space is established for a table fragment, that for each table in the database, the data of the table is stored in one or more main table fragment in the main store and in one or more delta table fragments in the delta store. Each table fragment has a local RID space, and the local RID space is a collection of one-based contiguous integer local RIDs (Row IDs) describing local positions of the rows of the table fragment.

Abstract: Dynamically directing a command to a node in a distributed database is described. An example method includes receiving the command from a client application to access data in the distributed database, where the command contains a set of parameters. A primary key is constructed from at least some of the parameters. The client further generates routing information from a node-partition table based on a comparison of the primary key with an entry in the node-partition table, where the node-partition table maps the primary key to a node in the distributed database. Accordingly, the command is directed to the node in the distributed database based on the routing information.

Abstract: A request for an entry of a dictionary having multiple dictionary blocks may be received, where the dictionary stores string values associated with corresponding value identifiers (IDs) for dictionary compression. One of the dictionary blocks may be selectively loaded into memory, and the dictionary block that has been loaded into memory may be searched. A value ID directory may be constructed in memory, where the value ID directory includes last value IDs for the dictionary blocks, and each of the last value IDs is mapped to an index of one of the dictionary blocks that includes a string value for that last value ID. A separator directory may also be constructed in memory, where the separator directory includes separators for the dictionary blocks, and each of the separators is mapped to an index of one of the dictionary blocks that includes a string value for that separator.

Abstract: Techniques for handling large string values in a string dictionary within an in-memory database system are presented. The string dictionary can be a paged-column main dictionary. For example, a value block of a dictionary may be loaded into memory, where the dictionary stores values for dictionary compression. The value block may include a first portion of a large string value and one or more logical pointers to one or more large string pages containing a remainder of the large string value. The large string value may be materialized into a contiguous location in memory, and a pointer to the materialized large string value may be created.

Abstract: Disclosed herein are system, method, and computer program product embodiments for populating a hash index and returning a handle to the hash index. An embodiment operates by determining, by at least one processor, during query optimization that a first database query has a query execution plan comprising a sub-query which executes N times a correlated predicate having an operator being one of equal and not equal to a base column. A cost of creating and probing the hash index N times and a cost of fully scanning the base column N times are compared based on the correlated predicate. Based on the comparing, it is determined whether to create on-demand a hash index.

Abstract: A delta store giving row-level versioning semantics to a non-row-level versioning underlying store is described. An example method includes establishing a column-based in-memory database including a main store and a delta store, where the main store does not allow concurrent transactions on a same table and the delta store has a plurality of row-visibility bitmaps implementing a row-level versioning mechanism that allows concurrent transactions on the same table. A transaction associated with the column-based in-memory database is received. For each table read by the transaction, a version of the table in the delta store that represents a transaction-consistent snapshot of the database visible to the transaction is determined. Each table is represented in the main store and the delta store; and each version of the table is represented by one or more bitmaps.

Abstract: Disclosed herein are system, method, and computer program product embodiments for implementing a bitmap for a column store database. An embodiment operates by creating, by at least one processor, a bitmap identifying rows in a column store database. The bitmap may include a list of bit chunks, a bit chunk including an offset being a natural number indicating a chunk size, and a bit specification including one of an ordered row id list, a contiguous row id sequence, and a bit vector. In addition, the embodiment includes performing database operations using the bitmap.

Abstract: A system and methodology for parallel query optimization using semantic-based partitioning is described. In one embodiment, for example, in a database system comprising a database storing data in database tables, a method is described for improving query performance by dynamically partitioning the data, the method comprises steps of: receiving a query requesting data from the database; generating a plurality of subplans for executing the query, each subplan including one or more operators for performing relational operations; adding operators for partitioning data and performing a given relational operation in parallel to at least some of the plurality of subplans; and building a plan for execution of the query based, at least in part, upon selecting subplans having favorable execution costs.

Abstract: A database system with methodology for generating bushy nested loop join trees is described. In one embodiment, for example, an improved method is described for optimization of a query requesting data from a database, the method comprises steps of: generating a left deep operator tree for returning data requested by the query based on traversing a left deep operator tree search space; transforming the left deep operator tree into a semantically correct structure for returning data requested by the query; and building a query execution plan for returning data requested by the query based on the semantically correct structure.

Abstract: System and methodology for automatic tuning of database query optimizer is described.

Abstract: A system and methodology for parallel query optimization using semantic-based partitioning is described.

Abstract: A database system with methodology for generating bushy nested loop join trees is described. In one embodiment, for example, an improved method is described for optimization of a query requesting data from a database, the method comprises steps of: generating a left deep operator tree for returning data requested by the query based on traversing a left deep operator tree search space; transforming the left deep operator tree into a semantically correct structure for returning data requested by the query; and building a query execution plan for returning data requested by the query based on the semantically correct structure.

Abstract: A database system providing methods for eager and opportunistic property enforcement is described. Plan fragments are generated for obtaining data requested by a query. Plan fragments are grouped together in classes based upon tables of the database covered by each plan fragment. For each class, a particular plan fragment having the lowest execution costs for obtaining the data requested by the query is determined. If grouping is not required at a given class, an operator enforcing ordering is added to this particular sub-plan. However, if grouping is required at the given class, an operator enforcing both grouping and ordering is added to this sub-plan.

Abstract: A database system providing methods for eager and opportunistic property enforcement is described. Plan fragments are generated for obtaining data requested by a query. Plan fragments are grouped together in classes based upon tables of the database covered by each plan fragment. For each class, a particular plan fragment having the lowest execution costs for obtaining the data requested by the query is determined. If grouping is not required at a given class, an operator enforcing ordering is added to this particular sub-plan. However, if grouping is required at the given class, an operator enforcing both grouping and ordering is added to this sub-plan.

Abstract: A database system providing a methodology, implemented as an “Abstract Plan on Disc” technology (referred to herein as, “Ariadne”), is described for turning cost based optimization decisions into stored, reusable items. In particular, the present invention provides a novel language interface to the optimizer, through an Abstract Plan, through which it can be given a description of the desired query execution plan (QEP). The language interface defines a declarative language syntax that allows description of the QEP. It does not specify the sequence of operations the database system's optimizer and code generator should accomplish to generate the QEP, but rather describes the desired outcome. Such an approach provides an abstraction barrier between an optimizer directives language and some specific optimizer and code generator. In this manner, the present invention allows a database system the ability to generate a better execution plan, and thereby realize better query performance.