Abstract: Provided are techniques for estimating most frequent values. A sample of values made up of rows is received from each of multiple nodes. The sample of values from each of the multiple nodes are aggregated to generate a sample table storing the rows. A descending list of most frequent values and associated frequencies is obtained using the sample table. Most frequent values are pruned from the descending list whose associated frequencies are below a minimum absolute frequency. The remaining most frequent values are extrapolated to reflect a data set.

Abstract: A usage model and the underlying technology used to provide sequence analysis as part of a relational database system. Included components include the semantic and syntactic integration of the sequence analysis with an existing query language, the storage methods for the sequence data, and the design of a multipart execution scheme that runs the sequence analysis as part of a potentially larger database join, especially using parallel execution techniques.

Abstract: A usage model and the underlying technology used to provide sequence analysis as part of a relational database system. Included components include the semantic and syntactic integration of the sequence analysis with an existing query language, the storage methods for the sequence data, and the design of a multipart execution scheme that runs the sequence analysis as part of a potentially larger database join, especially using parallel execution techniques.

Abstract: A usage model and the underlying technology used to provide sequence analysis as part of a relational database system. Included components include the semantic and syntactic integration of the sequence analysis with an existing query language, the storage methods for the sequence data, and the design of a multipart execution scheme that runs the sequence analysis as part of a potentially larger database join, especially using parallel execution techniques.

Abstract: Provided are techniques for estimating most frequent values. A sample of values made up of rows is received from each of multiple nodes. The sample of values from each of the multiple nodes are aggregated to generate a sample table storing the rows. A descending list of most frequent values and associated frequencies is obtained using the sample table. Most frequent values are pruned from the descending list whose associated frequencies are below a minimum absolute frequency. The remaining most frequent values are extrapolated to reflect a data set.

Abstract: A usage model and the underlying technology used to provide sequence analysis as part of a relational database system. Included components include the semantic and syntactic integration of the sequence analysis with an existing query language, the storage methods for the sequence data, and the design of a multipart execution scheme that runs the sequence analysis as part of a potentially larger database join, especially using parallel execution techniques.

Abstract: Provided are techniques for estimating most frequent values. A sample of values made up of rows is received from each of multiple nodes. The sample of values from each of the multiple nodes are aggregated to generate a sample table storing the rows. A descending list of most frequent values and associated frequencies is obtained using the sample table. Most frequent values are pruned from the descending list whose associated frequencies are below a minimum absolute frequency. The remaining most frequent values are extrapolated to reflect a data set.

Abstract: A usage model and the underlying technology used to provide sequence analysis as part of a relational database system. Included components include the semantic and syntactic integration of the sequence analysis with an existing query language, the storage methods for the sequence data, and the design of a multipart execution scheme that runs the sequence analysis as part of a potentially larger database join, especially using parallel execution techniques.

Abstract: Provided are techniques for estimating most frequent values. A sample of values made up of rows is received from each of multiple nodes. The sample of values from each of the multiple nodes are aggregated to generate a sample table storing the rows. A descending list of most frequent values and associated frequencies is obtained using the sample table. Most frequent values are pruned from the descending list whose associated frequencies are below a minimum absolute frequency. The remaining most frequent values are extrapolated to reflect a data set.

Abstract: A usage model and the underlying technology used to provide sequence analysis as part of a relational database system. Included components include the semantic and syntactic integration of the sequence analysis with an existing query language, the storage methods for the sequence data, and the design of a multipart execution scheme that runs the sequence analysis as part of a potentially larger database query, especially using parallel execution techniques.

Abstract: A usage model and the underlying technology used to provide sequence analysis as part of a relational database system. Included components include the semantic and syntactic integration of the sequence analysis with an existing query language, the storage methods for the sequence data, and the design of a multipart execution scheme that runs the sequence analysis as part of a potentially larger database query, especially using parallel execution techniques.

Abstract: A usage model and the underlying technology used to provide sequence analysis as part of a relational database system. Included components include the semantic and syntactic integration of the sequence analysis with an existing query language, the storage methods for the sequence data, and the design of a multipart execution scheme that runs the sequence analysis as part of a potentially larger database query, especially using parallel execution techniques.

Abstract: An asymmetric data record processor and method includes host computers and Job processing units (JPU's) coupled together on a network. Each host computer and JPU forms a node on the network. A plurality of software operators allow each node to process streams of records. For each operator in a given sequence within nodes and across nodes, output of the operator is input to a respective succeeding operator. Data processing follows a logical data flow based on readiness of a record. As soon as a record is ready it is passed for processing from one part to a next part in the logical data flow. The flow of records during data processing is substantially continuous and of a streaming fashion.

Abstract: A usage model and the underlying technology used to provide sequence analysis as part of a relational database system. Included components include the semantic and syntactic integration of the sequence analysis with an existing query language, the storage methods for the sequence data, and the design of a multipart execution scheme that runs the sequence analysis as part of a potentially larger database query, especially using parallel execution techniques.

Abstract: A usage model and the underlying technology used to provide sequence analysis as part of a relational database system. Included components include the semantic and syntactic integration of the sequence analysis with an existing query language, the storage methods for the sequence data, and the design of a multipart execution scheme that runs the sequence analysis as part of a potentially larger database join, especially using parallel execution techniques.

Abstract: An asymmetric data record processor and method includes host computers and job processing units (JPU's) coupled together on a network. Each host computer and JPU forms a node on the network. A plurality of software operators allow each node to process streams of records. For each operator in a given sequence within nodes and across nodes, output of the operator is input to a respective succeeding operator. Data processing follows a logical data flow based on readiness of a record. As soon as a record is ready it is passed for processing from one part to a next part in the logical data flow. The flow of records during data processing is substantially continuous and of a streaming fashion.