Sap Se

George Mason Intellectual Properties, Inc.

Shiping Chen

Martin Heidel

Xinyuan Wang

Vivek Kandiyanallur

Ivan Schreter

Mihnea Andrei

Sushil Jajodia

Rolando Blanco

David Wein

Joern Schmidt

Peter Steinemann

Colin Florendo

Steffen Geissinger

Thorsten Glebe

Michael Muehle

Thomas Peh

Andreas Tonder

Chaitanya Gottipati

Christoph Roterring

Panfeng Zhou

Sarika Iyer

Nirvik Basak

Stephan Kottler

Xin Liu

Jörn Schmidt

Liang Song

Steffen Geiβinger

A computer implemented method for manipulating data comprises receiving log transaction information from a primary database system at a secondary database system and parsing the log transaction information to identify data objects that have been modified on the primary database system. The secondary database system determines whether the data objects are present in main memory on the secondary database system and whether the log transaction corresponds to a data manipulation language (DML) query or a data definition language (DDL) query. If the data objects are not in the main memory and the query is a DML query, they are copied from persistence data volumes to the main memory. The data objects in main memory are modified by replaying the log transactions on the data objects in the main memory. Then, the data objects in the persistence data volumes are modified. Related apparatus, systems, techniques and articles are also described.

Replay of redo log records in persistency or main memory of database systems

Restoring of a database table in the database system (e.g., an in-memory insert-only database system, etc.) is initiated. Thereafter, a transaction log volume storing data log records and multi-version concurrency control (MVCC) log records corresponding to the database table is accessed. Based on such access, data log records corresponding to the database table are replayed while insert and update MVCC log records corresponding to the database table are skipped. Subsequently, restoring of the database table in the database system is finalized. Related apparatus, systems, techniques and articles are also described.

Database redo log optimization by skipping MVCC redo log records

Disclosed herein are system, method, and computer program product embodiments for a database recovery and optimization with batch processing system. An embodiment operates by retrieving a database log that includes a plurality of operations for modifying data of a database stored across a plurality of tables. From the database log, a plurality of consecutive insert operations for inserting data into the database are identified. The consecutive insert operations are sorted by table. The sorted insert operations are grouped into a batch message. The batch message is transmit to the database for replay. An acknowledgement is received that the replay has completed.

Database recovery and optimization with batch processing

A computer implemented method for manipulating data comprises receiving log transaction information from a primary database system at a secondary database system and parsing the log transaction information to identify data objects that have been modified on the primary database system. The secondary database system determines whether the data objects are present in main memory on the secondary database system. If the data objects are not in the main memory, they are copied from persistence data volumes to the main memory. The data objects are modified by replaying the log transactions on the data objects in the main memory. Then, the data objects in the persistence data volumes are modified. Related apparatus, systems, techniques and articles are also described.

Common runtime and recovery framework for manipulating data in main memory of database systems

Disclosed herein are system, method, and computer program product embodiments for directly restoring a database from a log volume. An embodiment operates by reading one or more database transaction log records from a log volume. The embodiment then loads from a database table persistent storage one or more pages containing rows in the database table that will be read from or written to by the one or more database transaction log records. The embodiment then loads a dictionary for each column associated with the one or more database transaction log records. The embodiment then applies the one or more database transaction log records directly into the one or more loaded pages and the one or more dictionaries. Each dictionary and page modified in memory is then written to the database table persistent storage when a savepoint operation is performed.

Applying a database transaction log record directly to a database table container

Log records are accessed as part of a database operation in a database. The log records log insert, update, and delete operations in the database and include, for each row, a row position, a fragment identifier (ID), and a row ID. Thereafter, as part of the database operation, rows specified by the log records are located by: using the fragment identifier and the row position within the corresponding record of the log if the fragment with the corresponding fragment identifier is still available, otherwise, using the row identifier within the corresponding record of the log to look up the row position in an index of a corresponding row identifier column. The database operation is then finalized using the located rows. Related apparatus, systems, techniques and articles are also described.

Efficient database undo / redo logging

A packet flow side channel encoder and decoder embeds and extracts a side channel communication in an overt communication data stream transmitted over a network. The encoder selects more than one group of related packets being transmitted on the network, relates a packet of one group to a packet of another group to form a pair of packets; and delays the timing of at least one packet from each pair of packets The decoder determines inter-packet delays that are the difference in timing between two packets in a pair of packets; determines at least one inter-packet delay difference between two or more determined inter-packet delays; and extracts a bit using the at least one interpacket delay difference.

Packet flow side channel

An interval centroid-based watermark encoder encodes a watermark into a packet flow. Intervals are defined for the packet flow. Some of the intervals are selected as group A intervals while other intervals are selected as group B intervals. Group A and group B intervals are paired and assigned to watermark bits. A first or second value may be encoded by increasing the relative packet time between packets in either the group A (for the first bit value) or group B (for the second bit value) interval(s) of the interval pair(s) assigned to the watermark bits that are to represent the first or second bit value and the beginning of the same group interval(s). The relative packet times may be measured by a decoder and used to calculate a centroid difference for each interval pair. The centroid differences may be used to reconstruct the watermark.

Interval centroid based watermark decoder

Interval centroid based watermark

Growing community of inventors

Dublin, CA, United States of America

Shiping Chen