Abstract: A method implemented by at least one processing device, a processing device, and a computer program product are provided for adjusting hash partitions for a hash join operation. An amount of rows within each of an initial number of hash partitions is determined during assignment of respective rows to respective hash partitions. The initial number of hash partitions is adjusted to a final number of hash partitions based on the amount of rows within each of the initial number of hash partitions and an amount of available memory. The adjusting further includes determining the final number of hash partitions based on the amount of rows within each of the initial number of hash partitions and the amount of available memory, and assigning the rows to the final number of hash partitions. The hash join operation is then performed.

Abstract: A system for sorting in a column organized relational database by sorting only key columns in the column organized relational database to reduce memory and CPU usage. The sort may be performed using an in memory sort. After sorting the key columns, the system orders a payload column according to an order indicated by the key columns. The payload column is associated with the key columns in the column organized relational database. The system assesses memory capacity prior to ordering the payload column. Prior to ordering a plurality of payload columns, the system refrains from automatically concatenating the plurality of payload columns, and refrains from automatically de-concatenating any concatenated payload columns after the ordering the plurality of payload columns. The system determines an amount of required memory necessary to order the payload column, and detects an amount of available memory accessible to order the payload column.

Abstract: A system for sorting in a column organized relational database by sorting only key columns in the column organized relational database to reduce memory and CPU usage. The sort may be performed using an in memory sort. After sorting the key columns, the system orders a payload column according to an order indicated by the key columns. The payload column is associated with the key columns in the column organized relational database. The system assesses memory capacity prior to ordering the payload column. Prior to ordering a plurality of payload columns, the system refrains from automatically concatenating the plurality of payload columns, and refrains from automatically de-concatenating any concatenated payload columns after the ordering the plurality of payload columns. The system determines an amount of required memory necessary to order the payload column, and detects an amount of available memory accessible to order the payload column.

Abstract: A computer-implemented method includes receiving a query plan. The method includes identifying a plurality of qualified relevant rows and one or more encoding candidate payload columns. The method includes analyzing the relevant rows in the encoding candidate payload columns to yield a count of distinct contents and a payload column width. The method includes estimating a cost and determining whether the cost is larger than an amount of available memory for on-the-fly encoding all of the plurality of encoding candidate payload columns. The method is responsive to the estimated cost being less than the amount of available memory, by on-the-fly encoding the encoding candidates and responsive to the estimated cost being greater than the amount of available memory by on-the-fly encoding fewer than all of the encoding candidates so as not to exceed the available memory, and leaving alone one or more remaining encoding candidate payload columns unencoded.

Abstract: A computer-implemented method includes receiving a query plan. The method includes identifying a plurality of qualified relevant rows and one or more encoding candidate payload columns. The method includes analyzing the relevant rows in the encoding candidate payload columns to yield a count of distinct contents and a payload column width. The method includes estimating a cost and determining whether the cost is larger than an amount of available memory for on-the-fly encoding all of the plurality of encoding candidate payload columns. The method is responsive to the estimated cost being less than the amount of available memory, by on-the-fly encoding the encoding candidates and responsive to the estimated cost being greater than the amount of available memory by on-the-fly encoding fewer than all of the encoding candidates so as not to exceed the available memory, and leaving alone one or more remaining encoding candidate payload columns unencoded.

Abstract: A method implemented by at least one processing device, a processing device, and a computer program product are provided for adjusting hash partitions for a hash join operation. An amount of rows within each of an initial number of hash partitions is determined during assignment of respective rows to respective hash partitions. The initial number of hash partitions is adjusted to a final number of hash partitions based on the amount of rows within each of the initial number of hash partitions and an amount of available memory. The adjusting further includes determining the final number of hash partitions based on the amount of rows within each of the initial number of hash partitions and the amount of available memory, and assigning the rows to the final number of hash partitions. The hash join operation is then performed.

Abstract: A computer-implemented method includes receiving a query plan. The method includes identifying a plurality of qualified relevant rows and one or more encoding candidate payload columns. The method includes analyzing the relevant rows in the encoding candidate payload columns to yield a count of distinct contents and a payload column width. The method includes estimating a cost and determining whether the cost is larger than an amount of available memory for on-the-fly encoding all of the plurality of encoding candidate payload columns. The method is responsive to the estimated cost being less than the amount of available memory, by on-the-fly encoding the encoding candidates and responsive to the estimated cost being greater than the amount of available memory by on-the-fly encoding fewer than all of the encoding candidates so as not to exceed the available memory, and leaving alone one or more remaining encoding candidate payload columns unencoded.

Abstract: A computer-implemented method includes receiving a query plan. The method includes identifying a plurality of qualified relevant rows and one or more encoding candidate payload columns. The method includes analyzing the relevant rows in the encoding candidate payload columns to yield a count of distinct contents and a payload column width. The method includes estimating a cost and determining whether the cost is larger than an amount of available memory for on-the-fly encoding all of the plurality of encoding candidate payload columns. The method is responsive to the estimated cost being less than the amount of available memory, by on-the-fly encoding the encoding candidates and responsive to the estimated cost being greater than the amount of available memory by on-the-fly encoding fewer than all of the encoding candidates so as not to exceed the available memory, and leaving alone one or more remaining encoding candidate payload columns unencoded.

Abstract: A computer-implemented method includes receiving a query plan. The method includes identifying a plurality of qualified relevant rows and one or more encoding candidate payload columns. The method includes analyzing the relevant rows in the encoding candidate payload columns to yield a count of distinct contents and a payload column width. The method includes estimating a cost and determining whether the cost is larger than an amount of available memory for on-the-fly encoding all of the plurality of encoding candidate payload columns. The method is responsive to the estimated cost being less than the amount of available memory, by on-the-fly encoding the encoding candidates and responsive to the estimated cost being greater than the amount of available memory by on-the-fly encoding fewer than all of the encoding candidates so as not to exceed the available memory, and leaving alone one or more remaining encoding candidate payload columns unencoded.

Abstract: A computer-implemented method includes receiving a query plan. The method includes identifying a plurality of qualified relevant rows and one or more encoding candidate payload columns. The method includes analyzing the relevant rows in the encoding candidate payload columns to yield a count of distinct contents and a payload column width. The method includes estimating a cost and determining whether the cost is larger than an amount of available memory for on-the-fly encoding all of the plurality of encoding candidate payload columns. The method is responsive to the estimated cost being less than the amount of available memory, by on-the-fly encoding the encoding candidates and responsive to the estimated cost being greater than the amount of available memory by on-the-fly encoding fewer than all of the encoding candidates so as not to exceed the available memory, and leaving alone one or more remaining encoding candidate payload columns unencoded.

Abstract: A computer-implemented method includes receiving a query plan. The method includes identifying a plurality of qualified relevant rows and one or more encoding candidate payload columns. The method includes analyzing the relevant rows in the encoding candidate payload columns to yield a count of distinct contents and a payload column width. The method includes estimating a cost and determining whether the cost is larger than an amount of available memory for on-the-fly encoding all of the plurality of encoding candidate payload columns. The method is responsive to the estimated cost being less than the amount of available memory, by on-the-fly encoding the encoding candidates and responsive to the estimated cost being greater than the amount of available memory by on-the-fly encoding fewer than all of the encoding candidates so as not to exceed the available memory, and leaving alone one or more remaining encoding candidate payload columns unencoded.

Abstract: A system for sorting in a column organized relational database by sorting only key columns in the column organized relational database to reduce memory and CPU usage. The sort may be performed using an in memory sort. After sorting the key columns, the system orders a payload column according to an order indicated by the key columns. The payload column is associated with the key columns in the column organized relational database. The system assesses memory capacity prior to ordering the payload column. Prior to ordering a plurality of payload columns, the system refrains from automatically concatenating the plurality of payload columns, and refrains from automatically de-concatenating any concatenated payload columns after the ordering the plurality of payload columns. The system determines an amount of required memory necessary to order the payload column, and detects an amount of available memory accessible to order the payload column.

Abstract: A system for sorting in a column organized relational database by sorting only key columns in the column organized relational database to reduce memory and CPU usage. The sort may be performed using an in memory sort. After sorting the key columns, the system orders a payload column according to an order indicated by the key columns. The payload column is associated with the key columns in the column organized relational database. The system assesses memory capacity prior to ordering the payload column. Prior to ordering a plurality of payload columns, the system refrains from automatically concatenating the plurality of payload columns, and refrains from automatically de-concatenating any concatenated payload columns after the ordering the plurality of payload columns. The system determines an amount of required memory necessary to order the payload column, and detects an amount of available memory accessible to order the payload column.

Abstract: A method implemented by at least one processing device, a processing device, and a computer program product are provided for adjusting hash partitions for a hash join operation. An amount of rows within each of an initial number of hash partitions is determined during assignment of respective rows to respective hash partitions. The initial number of hash partitions is adjusted to a final number of hash partitions based on the amount of rows within each of the initial number of hash partitions and an amount of available memory. The adjusting further includes determining the final number of hash partitions based on the amount of rows within each of the initial number of hash partitions and the amount of available memory, and assigning the rows to the final number of hash partitions. The hash join operation is then performed.

Abstract: A method implemented by at least one processing device, a processing device, and a computer program product are provided for adjusting hash partitions for a hash join operation. An amount of rows within each of an initial number of hash partitions is determined during assignment of respective rows to respective hash partitions. The initial number of hash partitions is adjusted to a final number of hash partitions based on the amount of rows within each of the initial number of hash partitions and an amount of available memory. The adjusting further includes determining the final number of hash partitions based on the amount of rows within each of the initial number of hash partitions and the amount of available memory, and assigning the rows to the final number of hash partitions. The hash join operation is then performed.

Abstract: A computer-implemented method includes receiving a query plan. The method includes identifying a plurality of qualified relevant rows and one or more encoding candidate payload columns. The method includes analyzing the relevant rows in the encoding candidate payload columns to yield a count of distinct contents and a payload column width. The method includes estimating a cost and determining whether the cost is larger than an amount of available memory for on-the-fly encoding all of the plurality of encoding candidate payload columns. The method is responsive to the estimated cost being less than the amount of available memory, by on-the-fly encoding the encoding candidates and responsive to the estimated cost being greater than the amount of available memory by on-the-fly encoding fewer than all of the encoding candidates so as not to exceed the available memory, and leaving alone one or more remaining encoding candidate payload columns unencoded.

Abstract: Techniques are disclosed for accessing a dimensional data model when processing a query. In one embodiment, the query is processed by performing a two-stage zigzag join operation including a zigzag main join and a zigzag back join. The zigzag main join is configured to generate a set of row identifiers of fact records satisfying any local predicates in the query. The zigzag back join is configured to generate query results based on the set of row identifiers. The query results are returned responsive to the query.

Abstract: A query processing system has a query processor and a data manager. The query processor calls the data manager to carry out data access for a query including a filtering operation. The data manager accesses the data in a set of data and before returning the data, initiates a callback to the query processor to determine if the located data meets the filtering criteria. Where the data does not satisfy the filtering criteria, the data manager seeks additional data in the set of data, without having to return the first located data to the query processor.

Abstract: Methods and apparatus, including computer program products, implementing and using techniques for executing a query in a computer to retrieve data from a relational database stored on a data storage device. A query is received that contains a CASE expression having one or more subqueries. A query execution plan is generated. The query execution plan uses a parameterized union all operator to keep the semantics of the CASE expression, and a nested loop join operator to drive data across the section of the query execution plan that executes the CASE expression without performing any join operations. The generated query execution plan is executed in the computer to retrieve data from the relational database.

Abstract: Methods and apparatus, including computer program products, implementing and using techniques for executing a query in a computer to retrieve data from a relational database stored on a data storage device. A query is received that contains a CASE expression having one or more subqueries. A query execution plan is generated. The query execution plan uses a parameterized union all operator to keep the semantics of the CASE expression, and a nested loop join operator to drive data across the section of the query execution plan that executes the CASE expression without performing any join operations. The generated query execution plan is executed in the computer to retrieve data from the relational database.