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operating system may not have fully written the journal to disk. The "fast" option<br />
protects against MarkLogic Server process failures but not against host operating<br />
system kernel failures or host hardware failures. The "off" option does not journal<br />
at all and does not protect against MarkLogic Server process failures, host operating<br />
system kernel failures, or host hardware failures. For some specialized cases where<br />
the data is recoverable, such as during a bulk load, it may be appropriate to set<br />
journaling "off" temporarily to reduce disk activity and process overhead.<br />
5. Linux Huge Pages and Transparent Huge Pages: Linux Huge Pages are<br />
two-megabyte blocks of memory; normal pages are just four kilobytes. Besides<br />
being bigger, they also are locked in memory and cannot be paged out. Employing<br />
Huge Pages gives MarkLogic more efficient access to memory and also ensures that<br />
its in-memory data structures remain pegged in memory. MarkLogic recommends<br />
setting Linux Huge Pages to 3/8 the size of your physical memory and recommends<br />
against using Transparent Huge Pages, which while enabled by default on Red Hat<br />
6 are still buggy. You'll see advice to this effect in the ErrorLog.txt should MarkLogic<br />
detect anything less.<br />
6. Swap space: If the MarkLogic process uses all available memory, the OS will use<br />
swap space as a temporary memory store. Once this happens, things will get slow—<br />
very slow. Having swap space will allow your performance to gradually degrade<br />
over time instead of just crashing when the OS can't allocate more memory. If your<br />
hardware has less than 32 gigabytes RAM, then use 1x available RAM for swap. If<br />
your hardware has more than 32 gigabytes RAM, use 32 gigabytes RAM.<br />
7. Red Hat Linux deadline I/O scheduler: The deadline I/O scheduler improves<br />
performance and ensures that operations won't starve for resources and possibly never<br />
complete. On Red Hat Linux platforms, the deadline I/O scheduler is required.<br />
8. Forests: Forests are in most ways independent from each other, so with multi-core<br />
systems, you can often benefit by having more forests to get more parallel execution.<br />
Also, forests can be queried in parallel by different threads running on different<br />
cores. It's true that the stands within a forest can be queried in parallel by separate<br />
threads, but after a merge, there might be just one stand and so no chance for<br />
parallelization. This makes it important to configure a sufficient number of forests<br />
for your deployment.<br />
For more on best practices for optimizing MarkLogic performance, see the white paper<br />
Performance: Understanding System Resources.<br />
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