Hi!
I'm trying to make an index of several text documents.
Their content is just field tab-separated strings:
word<\t>w1<\t>w2<\t>...<\t>wn
pos<\t>pos1<\t>pos2_a:pos2_b:pos2_c<\t>...<\t>posn_a:posn_b
...
There are 5 documents with the total of 10 MB in size.
While indexing, java uses about 2 GB of RAM and finally thows an OOM error.
String join_token = tok.nextToken();
// atomic tokens correspond to separate parses
String[] atomic_tokens = StringUtils.split(join_token, ':');
// marking each token with the parse number
for (int token_index = 0; token_index < atomic_tokens.length;
++token_index) {
atomic_tokens[token_index] += String.format("|%d", token_index);
}
String join_token_with_payloads = StringUtils.join(atomic_tokens, " ");
>>>> TokenStream stream = new WhitespaceTokenizer(Version.LUCENE_41,
>>>> <<<< the line where the leak appears
new
StringReader(join_token_with_payloads));
// all these parses belong to the same position in the document
stream = new PositionFilter(stream, 0);
stream = new DelimitedPayloadTokenFilter(stream, '|', new
IntegerEncoder());
stream.addAttribute(OffsetAttribute.class);
stream.addAttribute(CharTermAttribute.class);
feature = new Field(name,
join_token,
attributeFieldType);
feature.setTokenStream(stream);
inDocument.add(feature);
What is wrong with this code from the memory point of view, and how to do
indexing with as little data as possible held in RAM?
--
Best Regards,
Igor Shalyminov
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