Oracle International Corporation

Roger Dermot Macnicol

Shasank Kisan Chavan

Amit Ganesh

Tirthankar Lahiri

Jesse Kamp

Xia Hua

Maria Colgan

Juan R Loaiza

Vikram Kapoor

Vineet Marwah

Kothanda Umamageswaran

Manosiz Bhattacharyya

Krishnan Meiyyappan

Allison Holloway

Ajit Mylavarapu

Kam Shergill

Sachin Kulkarni

Prashant Gaharwar

Viral Shah

Dennis Lui

Dina Thomas

Adrian Tsz Him Ng

Sheldon A K Lewis

Yiran Qin

Jesse Kemp

Techniques herein use in-memory column vectors to process data that is external to a database management system (DBMS) and logically join the external data with data that is native to the DBMS. In an embodiment, a computer maintains a data dictionary for native data that is durably stored in an DBMS and external data that is not durably stored in the DBMS. From a client through a connection to the DBMS, the computer receives a query. The computer loads the external data into an in-memory column vector that resides in random access memory of the DBMS. Based on the query and the data dictionary, the DBMS executes a data join of the in-memory column vector with the native data. To the client through said connection, the computer returns results of the query based on the data join.

Performing in-memory columnar analytic queries on externally resident data

Techniques are described herein for sharing a dictionary across multiple in-memory compression units (IMCUs). After a dictionary is used to encode a first column vector in a first IMCU, the same dictionary is used to encode a second column vector in a second IMCU. The entries in the dictionary are in sort order to facilitate binary searching when performing value-to-code look-ups. If, during the encoding of the second column vector, values are encountered for which the dictionary does not already have codes, then a 'sort-order-boundary' is established after the last entry in the dictionary, and entries for the newly encountered values are added to the dictionary, after the sort-order-boundary. To facilitate value-to-code look-ups, the new entries are also sorted relative to each other, creating a second 'sort order set'. A new version of the dictionary may be created when the number of sort order sets in the first version of the dictionary reaches a configurable threshold.

In-memory column-level multi-versioned global dictionary for in-memory databases

Techniques are provided for storing in in-memory unit (IMU) in a lower-storage tier and copying the IMU to DRAM when needed for query processing. Techniques are also provided for copying IMUs to lower tiers of storage when evicted from the cache of higher tiers of storage. Techniques are provided for implementing functionality of IMUs within a storage system, to enable database servers to push tasks, such as filtering, to the storage system where the storage system may access IMUs within its own memory to perform the tasks. Metadata associated with a set of data may be used to indicate whether an IMU for the data should be created by the database server machine or within the storage system.

Columnar caching in tiered storage

Techniques are described herein for automatically selecting the compression techniques to be used on tabular data. A compression analyzer gives users high-level control over the selection process without requiring the user to know details about the specific compression techniques that are available to the compression analyzer. Users are able to specify, for a given set of data, a 'balance point' along the spectrum between 'maximum performance' and &#x201c;maximum compression&#x201d;. The point thus selected is used by the compression analyzer in a variety of ways. For example, in one embodiment, the compression analyzer uses the user-specified balance point to determine which of the available compression techniques qualify as &#x201c;candidate techniques&#x201d; for the given set of data. The compression analyzer selects the compression technique to use on a set of data by actually testing the candidate compression techniques against samples from the set of data. After testing the candidate compression techniques against the samples, the resulting compression ratios are compared. The compression technique to use on the set of data is then selected based, in part, on the compression ratios achieved during the compression tests performed on the sample data.

Compression analyzer

Growing community of inventors

Stevens, PA, United States of America

Roger Dermot Macnicol