Abstract: A computer system receives a database query to be executed against a database having a database table that stores records associated with keys. The database query specifies a set of conditional expressions that affect which ones of those records are returned. Based on the set of conditional expressions, the computer system derives a set of key ranges. The deriving can include representing the set of conditional expressions as a set of key spaces, performing a set of logical operations on pairs of those key spaces to reduce a number of key spaces in the set of key spaces, and converting the set of key spaces into the set of key ranges after performing the set of logical operations.

Abstract: Techniques are disclosed relating to deriving a set of key ranges. A computer system receives a database query to be executed against a database having a database table that stores records associated with keys. The database query specifies a set of conditional expressions that affect which ones of those records are returned. Based on the set of conditional expressions, the computer system derives a set of key ranges. The deriving can include representing the set of conditional expressions as a set of key spaces, performing a set of logical operations on pairs of those key spaces to reduce a number of key spaces in the set of key spaces, and converting the set of key spaces into the set of key ranges after performing the set of logical operations.

Abstract: Implementations are provided herein for causally ordering events within a distributed file system. Each node within the distributed file system, when processing an event, can collect object/version pairs associated with event (e.g., an object identifier and an object version number of the object at the time of the event). Object/version pairs can be identified and labeled as reliable or unreliable based on the operation performed on the inode as a part of the event. Relationships between events can be established when two events modify the same object and one event has a lower revision number. If the two object/revision pairs are in a relationship, an unreliable relationship can be deemed a weak edge and a reliable relationship can be deemed a strong edge. Using the strong and weak edges associated with object/revision pairs, a causal order of events can be generated.

Abstract: Implementations are provided herein for using inode revision numbers associated with a modified LIN and a set of Parent LINs to causally order transactions within a distributed file system. Any time an inode is changed, its inode revision number can be incremented by 1. When events within file system are processed causing an inode or a set of inodes to be modified, an event transaction log entry can made. The event transaction log entry can denote a description of the event, a set of modified inode and inode revision number pairs, and a set of parent inode and inode revision number pairs. Entries in the event transaction log can be used to build an inode map for each inode implicated in the event transaction log. The inode map can be used to build a set of direct causal dependencies for each transaction in the event transaction log.

Abstract: Implementations are provided herein for utilizing the two-part nature of HDFS protocol communications received in a non-native HDFS environment to use discriminative information learned in the NameNode request to make the client experience more efficient. NameNode requests can be received by any node among a cluster of nodes. It can be appreciated that in some non-native HDFS, clients can communicate with any nodes among a cluster to perform transactions and need not first communicate with a NameNode. Thus, upon receiving a NameNode request, the non-native HDFS Cluster of Nodes can prefetch data necessary from stable storage to cache memory for efficient reads and/or writes, allocate space on disk for writes, assign the client to communicate with a specific node among the cluster of nodes based on available cluster resources, etc. In this sense, a more efficient client experience can be offered for HDFS clients within a non-native HDFS environment.

Abstract: Implementations are provided herein for causally ordering events within a distributed file system. Each node within the distributed file system, when processing an event, can collect object/version pairs associated with event (e.g., an object identifier and an object version number of the object at the time of the event). Object/version pairs can be identified and labeled as reliable or unreliable based on the operation performed on the inode as a part of the event. Relationships between events can be established when two events modify the same object and one event has a lower revision number. If the two object/revision pairs are in a relationship, an unreliable relationship can be deemed a weak edge and a reliable relationship can be deemed a strong edge. Using the strong and weak edges associated with object/revision pairs, a causal order of events can be generated.