![]() This is a system-wide change. The index used to have a lexicon, mapping words to wordIds using a large in-memory hash table. This made index-construction easier, but it also added a fairly significant RAM penalty to both the index service and the loader. The new design moves to 64 bit word identifiers calculated using the murmur hash of the keyword, and an index construction based on merging smaller indices. It also became necessary half-way through to upgrade guice as its error reporting wasn't *quite* compatible with JDK20. |
||
---|---|---|
.. | ||
src | ||
build.gradle | ||
readme.md |
Array Library
The array library offers easy allocation of large memory mapped files
with much less performance overhead than the traditional buffers[pos/size].get(pos%size)
-style constructions
java often leads to given its suffocating 2 Gb ByteBuffer size limitation.
It accomplishes this by delegating block oerations down to the appropriate page. If the operation crosses a page boundary, it is not delegated and a bit slower.
The library is written in a fairly unidiomatic way to accomplish diamond inheritance.
Quick demo:
var array = LongArray.mmapForWriting(Path.of("/tmp/test"), 1<<16);
array.transformEach(50, 1000, (pos, val) -> Long.hashCode(pos));
array.quickSort(50, 1000);
if (array.binarySearch(array.get(100), 50, 1000) >= 0) {
System.out.println("Nevermind, I found it!");
}
array.range(50, 1000).fill(0, 950, 1);
array.forEach(0, 100, (pos, val) -> {
System.out.println(pos + ":" + val);
});
Query Buffers
The classes IntQueryBuffer and LongQueryBuffer are used heavily in the search engine's query processing.
They are dual-pointer buffers that offer tools for filtering data.
LongQueryBuffer buffer = new LongQueryBuffer(1000);
// later ...
// Prepare the buffer for filling
buffer.reset();
fillBufferSomehow(buffer);
// length is updated and data is set
// read pointer and write pointer is now at 0
// A typical filtering operation may look like this:
while (buffer.hasMore()) { // read < end
if (someCondition(buffer.currentValue())) {
// copy the value pointed to by the read
// pointer to the read pointer, and
// advance both
buffer.retainAndAdvance();
}
else {
// advance the read pointer
buffer.rejectAndAdvance();
}
}
// set end to the write pointer, and
// resets the read and write pointers
buffer.finalizeFiltering();
// ... after this we can filter again, or
// consume the data
Especially noteworthy are the operations retain()
and reject()
in
IntArraySearch and LongArraySearch.
They keep or remove all items in the buffer that exist in the referenced range of the array,
which must be sorted.
These are used to offer an intersection operation for the B-Tree with sub-linear run time.