Integrate Waterloo spam scores and other static priors into index

[castorini]

Integrate Waterloo spam scores and other static priors into index

[lintool]

This is probably the right way to implement this: https://lucene.apache.org/core/8_11_0/core/org/apache/lucene/document/FeatureField.html

[iorixxx]

Here is what I do for the spam rankings: I split huge (15BG) spamFusion file into chunks, these chunks (spam scores) are saved into a directory structure that is identical to the ClueWeb09B *.warc directory structure.

To perform the aforementioned operation, I rely on voldemort to store docID, and spamScore pairs of category B.

However, when dealing with category A, voldemort can be the only source during indexing. No need to dump data into files into a directory structure that is identical to CW09B.

What do you think about storing spam scores, in key value database such as voldemort?
For fast retrieval during indexing and/or searching?

Is this feasible ? Or generic enough?

[lintool]

Hrm... that's pretty heavyweight and requires an external dependency. I suppose for catB everything can fit in memory. Perhaps we can assume the same for catA? 500m * ( 2 bytes for value + 4 bytes for key) = 30 GB... reasonable on a server?

[iorixxx]

My ClueWeb09B_SpamFusion (contains chunks) directory is 1.4G in size. Indexer loads a single chunk file per a warc file. So memory won't be a problem. But preparing these chunks ( aligned with the warc files ) is heavy. I again rely on voldemort for producing chunks.

Here by saying chunk : I mean a miniature spam ranking file just for a single warc file.

[iorixxx]

It looks like, we can resolve warc folder path for a given docid deterministically.
e.g. docid = clueweb09-en0000-00-35369
path = ClueWeb09_English_1/en0000/00.war.gz

Then we can create miniature fusion files from the clueweb09spam.Fusion directly?

Spam scores will be used for skipping documents (given threshold ) during indexing?

[lintool]

I'd rather index everything and use spam as a feature during retrieval. That way we don't need to develop a cutoff.

[iorixxx]

aha I see. So you just want to percolate the result list?
Then we need ability to query arbitrary document id.
I cannot think of a solution without a key-value database or something.
How about we index spam rankings with lucene? for arbitrary lookup?

[lintool]

Just a big hashmap we load into memory at startup? Using, fastuil, for example?

[iorixxx]

Let me try fastutil tomorrow. If it does not blow the memory that would be the best solution.

[iorixxx]

I played with Object2IntOpenHashMap<String> however following program java -server -Xmx20g resulted in out of memory error. I think, even if we don't insert into a map, just sequentially traversing this big file will take time. What is the preferred course of action here?

/**
     * Try to load clueweb09spam.Fusion (15 GB) file to memory
     *
     * @param clueweb09spam spam file name
     * @throws IOException
     */
 public static void loadSpamFusion(String clueweb09spam) throws IOException {

        Object2IntOpenHashMap<String> map = new Object2IntOpenHashMap<>();

        Path clueweb09spamFusion = Paths.get(clueweb09spam);

        if (!Files.isRegularFile(clueweb09spamFusion) || !Files.exists(clueweb09spamFusion) || !Files.isReadable(clueweb09spamFusion))
            throw new IllegalArgumentException(clueweb09spamFusion + " does not exist or is not a file");


        try (BufferedReader reader = Files.newBufferedReader(clueweb09spamFusion, StandardCharsets.US_ASCII)) {

            for (; ; ) {
                String line = reader.readLine();
                if (line == null)
                    break;

                // lines with the following format: percentile-score clueweb-docid
                String[] parts = line.split("\\s+");
                map.put(parts[1], Integer.parseInt(parts[0]));
            }
        }

        System.out.println(map.size() + "many entries loaded into the map");
        map.clear();
    }

[lintool]

How much memory do you have on your machine?
The machine I use at UMD has 0.75 TB RAM :)

[iorixxx]

I have 64 GB :) Is there a maximum -Xmx value we should aim here?
Can you try the loading code? I wonder how much heap it will take.

[lintool]

Try using max heap?

[iorixxx]

with 80GB, 503903810 many entries loaded into the map in 00:42:27. If you think this resource is reasonable, I can replace voldemort with fastutil map in the code that percolates trec submission file.

[iorixxx]

I found a better data structure ReferenceOpenHashSet<String> for the task. I am abandoning voldemort for my self too. The program will take three arguments : spam threshold, submission file and waterloo spam scores file/folder. And then it will remove spammiest documents from the submission file. Does this reasonable?

[lintool]

Hi @iorixxx sorry for the late reply - was at TREC and starting to dig out of a backlog. Yes, this seems reasonable!