Elasticsearch B.v.

Sean Heelan

Thomas Dullien

In various embodiments, the system and method described herein provide functionality for selecting an appropriate compression algorithm and settings given a cost model. Specifically, in selecting a compression method and configuration, the described system and method use a cost model to take into account the financial cost of a number of aspects of a particular compression scenario, including, but not limited to, the cost of performing the compression/decompression and the cost of storing the data. In this manner, intelligent trade-offs can be made between CPU/computing cost and data storage/transmission cost in an environment where a dollar amount can be associated with CPU processing time and storage/transmission volume. The described system and method can make such decisions dynamically, so that compression and/or decompression operations can respond to changing conditions on the fly, thus leading to better and more cost-effective management of resources.

Selecting data compression parameters using a cost model

Functionality is provided for unwinding program call stacks across native-to-interpreted code and native-to-JIT-compiled code boundaries, as well as across the kernel and user space boundaries, during performance profiling. The system thus enables profiling of code that crosses boundaries from native code to interpreted languages and native code to languages that run on a runtime supporting JIT compilation. Various embodiments provide cross-language profiling with a sufficiently low performance impact so as to enable such profiling to take place in a production environment.

Unwinding program call stacks for performance profiling

Functionality is provided for profiling code by unwinding stacks in frame-pointer omitted executables using C++ exception stack unwinding information. Information is extracted from executable files, and used to optimize stack unwinding operations. In at least one embodiment, the system uses information that has been included for exception handling. Storage of such information can be optimized by exploiting patterns in stack deltas.

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Oxford, United Kingdom

Sean Heelan