Abstract: Executing a query in a disaggregated cluster. A query plan for a query is received at a disaggregated cluster that comprises compute node(s) and storage node(s). The query plan describes (a) the computation to be performed represented as a query tree which comprises a hierarchy of vertices, each of which corresponds to a query operator that is responsible for executing a portion of the query and (b) data sets to which the query requires access. Each execution engine instance optimizes execution of query fragments of the query plan by utilizing local resources to (a) create and execute parallel pipelines of sequences of native operators corresponding to vertices of linear subtrees of a query plan fragment and (b) prefetch data sets identified as being responsive to at least a portion of the query fragment from at least one storage node. A result is obtained and provided.

Abstract: Executing a query in a disaggregated cluster. A query is received at the disaggregated cluster. A query graph is created based on the query that identifies a hierarchy of vertices, where each vertex is associated with a set of data responsive to at least a portion of the query. The compute nodes process the query graph by first identifying a minimum set of tables, files, and objects stored on the storage nodes required to retrieve data that satisfy the query. Next, the compute nodes selectively assign the identified tables, files, and objects to a leaf vertex of the query graph to optimize retrieving data from the storage nodes. Thereafter, the compute nodes process the retrieved data sets associated with each vertex using separate threads of execution for each vertex of the query graph such that leaf vertices are performed in parallel. The compute nodes then provide a result set.

Abstract: Executing a query in a disaggregated cluster. A query is received at the disaggregated cluster. A query graph is created based on the query that identifies a hierarchy of vertices, where each vertex is associated with a set of data responsive to at least a portion of the query. The compute nodes process the query graph by first identifying all tables, files, and objects stored on the storage nodes whose access is required to retrieve data that satisfy the query. Next, the compute nodes selectively assign the identified tables, files, and objects to a leaf vertex of the query graph to optimize retrieving data from the storage nodes. Thereafter, the compute nodes process the retrieved data sets associated with each vertex using separate threads of execution for each vertex of the query graph such that leaf vertices are performed in parallel. The compute nodes then provide a result set.