Pivotal Software, Inc.

Swapnil Prakash Bawaskar

Jagannathan Ramnarayanan

Daniel Allen Smith

Hemant Bhanawat

Anthony M Baker

Ashvin Agrawal

Sumedh Wale

Neeraj Kumar

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for a distributed parallel processing database system that persists table data in memory to a distributed file system. A distributed parallel processing database system persists table data in memory to a distributed file system. A parameter of creating a database table specifies that data records in the database table and history of changes to the data records can be stored in memory as well as in the distributed file system. When the database table is populated or otherwise modified, data records and the history in memory are evicted to the distributed file system as log files and removed from memory. The log files can be designated as write-only, where the data records, once written, cannot be read by structured query language (SQL) queries, or as read-write, where the data records, once written, can be read by SQL queries.

Table data persistence

Systems, methods, and computer program products of distributing sorted sets to multiple nodes of a distributed in-memory database system are described. The distributed in-memory database system is a database system based on key-value pairs. The system receives data records including user data and scores for sorting. The system maps the user data to keys in the key-value pairs. The system maps the scores to the values in the key-value pairs. The system then distributes the mapped key-value pairs to the nodes. The distributed in-memory database system is indexed on the values.

Distributed sorted set

Methods, systems, and apparatus for obtaining one or more metadata files, determining, by one or more computers and in accordance with a minor compaction setting, to perform a minor compaction of the one or more metadata files, creating one or more intermediate metadata files that each include at least compacted contacts of one or more of the metadata files, according to the determination to perform minor compaction of the one or more metadata files, determining, in accordance with a major compaction setting, to perform a major compaction of one or more of the intermediate metadata files, and creating one or more snapshot metadata files that each include at least compacted contents of one or more of the intermediate metadata files, according to the determination to perform the major compaction of one or more of the intermediate metadata files.

Compacting data history files

Methods, systems, and apparatus for identifying two or more files, each of which include multiple entries, determining a respective size of each of the files, each size being an estimate of how many distinct entries exist in the respective file that are not garbage entries, determining a combined size of the files, where the combined size of the files is an arithmetic sum of the respective sizes of the files, estimating a compacted size of the files, where the estimated compacted size of the files is an estimate of how many distinct entries exist in the files that are not garbage entries, selecting the two or more files for compaction, based at least on a comparison of the combined size of the files to the estimated compacted size of the files, and compacting the two or more selected files.

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Hillsboro, OR, United States of America

Swapnil Prakash Bawaskar