Abstract: Example implementations relate to a database and a data stream query. For example, a computing device may include a processor. The processor may receive a query associated with at least one of a database and a buffer storing streamed data from a data stream, where the database stores database data previously stored in the buffer. The processor may identify at least one postponed command relevant to the query, the at least one postponed command being associated with at least one of the database data and the streamed data. The processor may generate a modified query based on the query and the at least one postponed command, the modified query being a modification of the query to account for the at least one postponed command. The processor may process the modified query and provide a query result of the query based on the modified query being processed.

Abstract: Example implementations relate to processing a query of a database and a data stream. For example, a computing device may include a processor. The processor may receive a query associated with at least one of a database and a buffer storing streamed data from a data stream. The database may store database data previously stored in the buffer. The processor may identify a range associated with the query and generate a set of sub-queries including at least one of a buffer sub-query if the range is associated with the streamed data in the buffer and a database sub-query if the range is associated with the database data in the database. The processor may process the set of sub-queries and provide a query result of the query, where the query result is a combination of sub-query results of the set of sub-queries.

Abstract: Processing a data flow graph of a hybrid flow can include a data structure to store metadata for each of a plurality of nodes of a data flow graph of a hybrid flow, processing the data flow graph of the hybrid flow, and defining metadata in the data structure for a particular node affected during processing of the data flow graph of the hybrid flow.

Abstract: Example implementations relate to a database and a data stream query. For example, a computing device may include a processor. The processor may receive a query associated with at least one of a database and a buffer storing streamed data from a data stream, where the database stores database data previously stored in the buffer. The processor may identify at least one postponed command relevant to the query, the at least one postponed command being associated with at least one of the database data and the streamed data. The processor may generate a modified query based on the query and the at least one postponed command, the modified query being a modification of the query to account for the at least one postponed command. The processor may process the modified query and provide a query result of the query based on the modified query being processed.

Abstract: Example implementations relate to a database and a data stream query. For example, a computing device may include a processor. The processor may receive a query associated with at least one of a database and a buffer storing streamed data from a data stream, where the database stores database data previously stored in the buffer. The processor may identify at least one postponed command relevant to the query, the at least one postponed command being associated with at least one of the database data and the streamed data. The processor may generate a modified query based on the query and the at least one postponed command, the modified query being a modification of the query to account for the at least one postponed command. The processor may process the modified query and provide a query result of the query based on the modified query being processed.

Abstract: Example implementations relate to a database and a data stream query. For example, a computing device may include a processor. The processor may receive a query associated with at least one of a database and a buffer storing streamed data from a data stream, where the database stores database data previously stored in the buffer. The processor may identify at least one postponed command relevant to the query, the at least one postponed command being associated with at least one of the database data and the streamed data. The processor may generate a modified query based on the query and the at least one postponed command, the modified query being a modification of the query to account for the at least one postponed command. The processor may process the modified query and provide a query result of the query based on the modified query being processed.

Abstract: Example implementations relate to processing a query of a database and a data stream. For example, a computing device may include a processor. The processor may receive a query associated with at least one of a database and a buffer storing streamed data from a data stream. The database may store database data previously stored in the buffer. The processor may identify a range associated with the query and generate a set of sub-queries including at least one of a buffer sub-query if the range is associated with the streamed data in the buffer and a database sub-query if the range is associated with the database data in the database. The processor may process the set of sub-queries and provide a query result of the query, where the query result is a combination of sub-query results of the set of sub-queries.

Abstract: A method for surrogate key generation performed by a physical computing system includes creating a lookup record for a production key of an input record, a key of the lookup record including the production key and a value of the lookup record including both a record identifier for the input record and a unique identifier of the production key within the input record. The method further includes sending the lookup record to a first node of a distributed computing system, the first node determined by hashing the production key with a first hash function, and with the first node, determining a surrogate key for the production key.

Abstract: Processing a data flow graph of a hybrid flow can include a data structure to store metadata for each of a plurality of nodes of a data flow graph of a hybrid flow, processing the data flow graph of the hybrid flow, and defining metadata in the data structure for a particular node affected during processing of the data flow graph of the hybrid flow.

Abstract: A method for data flow processing includes determining values for each of a set of parameters associated with a task within a data flow processing job, and applying a set of rules to determine one of a set of processing techniques that will be used to execute the task. The set of rules is determined through a set of benchmark tests for the task using each of the set of processing techniques while varying the set of parameters.

Abstract: A method for data flow processing includes determining values for each of a set of parameters associated with a task within a data flow processing job, and applying a set of rules to determine one of a set of processing techniques that will be used to execute the task. The set of rules is determined through a set of benchmark tests for the task using each of the set of processing techniques while varying the set of parameters.

Abstract: A method for surrogate key generation performed by a physical computing system includes creating a lookup record for a production key of an input record, a key of the lookup record including the production key and a value of the lookup record including both a record identifier for the input record and a unique identifier of the production key within the input record. The method further includes sending the lookup record to a first node of a distributed computing system, the first node determined by hashing the production key with a first hash function, and with the first node, determining a surrogate key for the production key.