Examples with BooleanEvaluator org.apache.solr.client.solrj.io.eval.BooleanEvaluator used on opensource projects

Example 1 with BooleanEvaluator

use of org.apache.solr.client.solrj.io.eval.BooleanEvaluator in project lucene-solr by apache.

the class SolrTable method handleGroupByMapReduce.

private TupleStream handleGroupByMapReduce(String zk, String collection, Properties properties, final List<Map.Entry<String, Class>> fields, final String query, final List<Pair<String, String>> orders, final List<String> _buckets, final List<Pair<String, String>> metricPairs, final String limit, final String havingPredicate) throws IOException {
    Map<String, Class> fmap = new HashMap();
    for (Map.Entry<String, Class> entry : fields) {
        fmap.put(entry.getKey(), entry.getValue());
    }
    int numWorkers = Integer.parseInt(properties.getProperty("numWorkers", "1"));
    Bucket[] buckets = buildBuckets(_buckets, fields);
    Metric[] metrics = buildMetrics(metricPairs, false).toArray(new Metric[0]);
    if (metrics.length == 0) {
        return handleSelectDistinctMapReduce(zk, collection, properties, fields, query, orders, buckets, limit);
    } else {
        for (Metric metric : metrics) {
            Class c = fmap.get(metric.getIdentifier());
            if (Long.class.equals(c)) {
                metric.outputLong = true;
            }
        }
    }
    Set<String> fieldSet = getFieldSet(metrics, fields);
    if (metrics.length == 0) {
        throw new IOException("Group by queries must include atleast one aggregate function.");
    }
    String fl = getFields(fieldSet);
    String sortDirection = getSortDirection(orders);
    String sort = bucketSort(buckets, sortDirection);
    ModifiableSolrParams params = new ModifiableSolrParams();
    params.set(CommonParams.FL, fl);
    params.set(CommonParams.Q, query);
    params.set(CommonParams.WT, CommonParams.JAVABIN);
    //Always use the /export handler for Group By Queries because it requires exporting full result sets.
    params.set(CommonParams.QT, "/export");
    if (numWorkers > 1) {
        params.set("partitionKeys", getPartitionKeys(buckets));
    }
    params.set(SORT, sort);
    TupleStream tupleStream = null;
    CloudSolrStream cstream = new CloudSolrStream(zk, collection, params);
    tupleStream = new RollupStream(cstream, buckets, metrics);
    StreamFactory factory = new StreamFactory().withFunctionName("search", CloudSolrStream.class).withFunctionName("parallel", ParallelStream.class).withFunctionName("rollup", RollupStream.class).withFunctionName("sum", SumMetric.class).withFunctionName("min", MinMetric.class).withFunctionName("max", MaxMetric.class).withFunctionName("avg", MeanMetric.class).withFunctionName("count", CountMetric.class).withFunctionName("and", AndEvaluator.class).withFunctionName("or", OrEvaluator.class).withFunctionName("not", NotEvaluator.class).withFunctionName("eq", EqualsEvaluator.class).withFunctionName("gt", GreaterThanEvaluator.class).withFunctionName("lt", LessThanEvaluator.class).withFunctionName("val", RawValueEvaluator.class).withFunctionName("lteq", LessThanEqualToEvaluator.class).withFunctionName("having", HavingStream.class).withFunctionName("gteq", GreaterThanEqualToEvaluator.class);
    if (havingPredicate != null) {
        BooleanEvaluator booleanOperation = (BooleanEvaluator) factory.constructEvaluator(StreamExpressionParser.parse(havingPredicate));
        tupleStream = new HavingStream(tupleStream, booleanOperation);
    }
    if (numWorkers > 1) {
        // Do the rollups in parallel
        // Maintain the sort of the Tuples coming from the workers.
        StreamComparator comp = bucketSortComp(buckets, sortDirection);
        ParallelStream parallelStream = new ParallelStream(zk, collection, tupleStream, numWorkers, comp);
        parallelStream.setStreamFactory(factory);
        tupleStream = parallelStream;
    }
    if (orders != null && orders.size() > 0) {
        if (!sortsEqual(buckets, sortDirection, orders)) {
            int lim = (limit == null) ? 100 : Integer.parseInt(limit);
            StreamComparator comp = getComp(orders);
            //Rank the Tuples
            //If parallel stream is used ALL the Rolled up tuples from the workers will be ranked
            //Providing a true Top or Bottom.
            tupleStream = new RankStream(tupleStream, lim, comp);
        } else {
            // Only need to limit the result, not Rank the result
            if (limit != null) {
                tupleStream = new LimitStream(tupleStream, Integer.parseInt(limit));
            }
        }
    } else {
        //No order by, check for limit
        if (limit != null) {
            tupleStream = new LimitStream(tupleStream, Integer.parseInt(limit));
        }
    }
    return tupleStream;
}

Example 2 with BooleanEvaluator

use of org.apache.solr.client.solrj.io.eval.BooleanEvaluator in project lucene-solr by apache.

the class SolrTable method handleGroupByFacet.

private TupleStream handleGroupByFacet(String zkHost, String collection, final List<Map.Entry<String, Class>> fields, final String query, final List<Pair<String, String>> orders, final List<String> bucketFields, final List<Pair<String, String>> metricPairs, final String lim, final String havingPredicate) throws IOException {
    Map<String, Class> fmap = new HashMap();
    for (Map.Entry<String, Class> f : fields) {
        fmap.put(f.getKey(), f.getValue());
    }
    ModifiableSolrParams solrParams = new ModifiableSolrParams();
    solrParams.add(CommonParams.Q, query);
    Bucket[] buckets = buildBuckets(bucketFields, fields);
    Metric[] metrics = buildMetrics(metricPairs, true).toArray(new Metric[0]);
    if (metrics.length == 0) {
        metrics = new Metric[1];
        metrics[0] = new CountMetric();
    } else {
        for (Metric metric : metrics) {
            Class c = fmap.get(metric.getIdentifier());
            if (Long.class.equals(c)) {
                metric.outputLong = true;
            }
        }
    }
    int limit = lim != null ? Integer.parseInt(lim) : 1000;
    FieldComparator[] sorts = null;
    if (orders == null || orders.size() == 0) {
        sorts = new FieldComparator[buckets.length];
        for (int i = 0; i < sorts.length; i++) {
            sorts[i] = new FieldComparator("index", ComparatorOrder.ASCENDING);
        }
    } else {
        sorts = getComps(orders);
    }
    int overfetch = (int) (limit * 1.25);
    TupleStream tupleStream = new FacetStream(zkHost, collection, solrParams, buckets, metrics, sorts, overfetch);
    StreamFactory factory = new StreamFactory().withFunctionName("search", CloudSolrStream.class).withFunctionName("parallel", ParallelStream.class).withFunctionName("rollup", RollupStream.class).withFunctionName("sum", SumMetric.class).withFunctionName("min", MinMetric.class).withFunctionName("max", MaxMetric.class).withFunctionName("avg", MeanMetric.class).withFunctionName("count", CountMetric.class).withFunctionName("and", AndEvaluator.class).withFunctionName("or", OrEvaluator.class).withFunctionName("not", NotEvaluator.class).withFunctionName("eq", EqualsEvaluator.class).withFunctionName("val", RawValueEvaluator.class).withFunctionName("gt", GreaterThanEvaluator.class).withFunctionName("lt", LessThanEvaluator.class).withFunctionName("lteq", LessThanEqualToEvaluator.class).withFunctionName("gteq", GreaterThanEqualToEvaluator.class);
    if (havingPredicate != null) {
        BooleanEvaluator booleanOperation = (BooleanEvaluator) factory.constructEvaluator(StreamExpressionParser.parse(havingPredicate));
        tupleStream = new HavingStream(tupleStream, booleanOperation);
    }
    if (lim != null) {
        tupleStream = new LimitStream(tupleStream, limit);
    }
    return tupleStream;
}