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The Apache Cassandra Project develops a highly scalable second-generation distributed database, bringing together Dynamo's fully distributed design and Bigtable's ColumnFamily-based data model.
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/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package org.apache.cassandra.service.pager;

import org.apache.cassandra.transport.ProtocolVersion;
import org.apache.cassandra.utils.AbstractIterator;

import java.util.Arrays;

import org.apache.cassandra.db.*;
import org.apache.cassandra.db.rows.*;
import org.apache.cassandra.db.filter.DataLimits;
import org.apache.cassandra.db.partitions.*;
import org.apache.cassandra.exceptions.RequestValidationException;
import org.apache.cassandra.exceptions.RequestExecutionException;
import org.apache.cassandra.service.ClientState;

/**
 * Pager over a list of SinglePartitionReadQuery.
 *
 * Note that this is not easy to make efficient. Indeed, we need to page the first query fully before
 * returning results from the next one, but if the result returned by each query is small (compared to pageSize),
 * paging the queries one at a time under-performs compared to parallelizing. On the other, if we parallelize
 * and each query raised pageSize results, we'll end up with queries.size() * pageSize results in memory, which
 * defeats the purpose of paging.
 *
 * For now, we keep it simple (somewhat) and just do one query at a time. Provided that we make sure to not
 * create a pager unless we need to, this is probably fine. Though if we later want to get fancy, we could use the
 * cfs meanPartitionSize to decide if parallelizing some of the query might be worth it while being confident we don't
 * blow out memory.
 */
public class MultiPartitionPager implements QueryPager
{
    private final SinglePartitionPager[] pagers;
    private final DataLimits limit;

    private final int nowInSec;

    private int remaining;
    private int current;

    public MultiPartitionPager(SinglePartitionReadQuery.Group group, PagingState state, ProtocolVersion protocolVersion)
    {
        this.limit = group.limits();
        this.nowInSec = group.nowInSec();

        int i = 0;
        // If it's not the beginning (state != null), we need to find where we were and skip previous queries
        // since they are done.
        if (state != null)
            for (; i < group.queries.size(); i++)
                if (group.queries.get(i).partitionKey().getKey().equals(state.partitionKey))
                    break;

        if (i >= group.queries.size())
        {
            pagers = null;
            return;
        }

        pagers = new SinglePartitionPager[group.queries.size() - i];
        // 'i' is on the first non exhausted pager for the previous page (or the first one)
        T query = group.queries.get(i);
        pagers[0] = query.getPager(state, protocolVersion);

        // Following ones haven't been started yet
        for (int j = i + 1; j < group.queries.size(); j++)
            pagers[j - i] = group.queries.get(j).getPager(null, protocolVersion);

        remaining = state == null ? limit.count() : state.remaining;
    }

    private MultiPartitionPager(SinglePartitionPager[] pagers,
                                DataLimits limit,
                                int nowInSec,
                                int remaining,
                                int current)
    {
        this.pagers = pagers;
        this.limit = limit;
        this.nowInSec = nowInSec;
        this.remaining = remaining;
        this.current = current;
    }

    public QueryPager withUpdatedLimit(DataLimits newLimits)
    {
        SinglePartitionPager[] newPagers = Arrays.copyOf(pagers, pagers.length);
        newPagers[current] = newPagers[current].withUpdatedLimit(newLimits);

        return new MultiPartitionPager(newPagers,
                                          newLimits,
                                          nowInSec,
                                          remaining,
                                          current);
    }

    public PagingState state()
    {
        // Sets current to the first non-exhausted pager
        if (isExhausted())
            return null;

        PagingState state = pagers[current].state();
        return new PagingState(pagers[current].key(), state == null ? null : state.rowMark, remaining, pagers[current].remainingInPartition());
    }

    public boolean isExhausted()
    {
        if (remaining <= 0 || pagers == null)
            return true;

        while (current < pagers.length)
        {
            if (!pagers[current].isExhausted())
                return false;

            current++;
        }
        return true;
    }

    public ReadExecutionController executionController()
    {
        // Note that for all pagers, the only difference is the partition key to which it applies, so in practice we
        // can use any of the sub-pager ReadOrderGroup group to protect the whole pager
        for (int i = current; i < pagers.length; i++)
        {
            if (pagers[i] != null)
                return pagers[i].executionController();
        }
        throw new AssertionError("Shouldn't be called on an exhausted pager");
    }

    @SuppressWarnings("resource") // iter closed via countingIter
    public PartitionIterator fetchPage(int pageSize, ConsistencyLevel consistency, ClientState clientState, long queryStartNanoTime) throws RequestValidationException, RequestExecutionException
    {
        int toQuery = Math.min(remaining, pageSize);
        return new PagersIterator(toQuery, consistency, clientState, null, queryStartNanoTime);
    }

    @SuppressWarnings("resource") // iter closed via countingIter
    public PartitionIterator fetchPageInternal(int pageSize, ReadExecutionController executionController) throws RequestValidationException, RequestExecutionException
    {
        int toQuery = Math.min(remaining, pageSize);
        return new PagersIterator(toQuery, null, null, executionController, System.nanoTime());
    }

    private class PagersIterator extends AbstractIterator implements PartitionIterator
    {
        private final int pageSize;
        private PartitionIterator result;
        private boolean closed;
        private final long queryStartNanoTime;

        // For "normal" queries
        private final ConsistencyLevel consistency;
        private final ClientState clientState;

        // For internal queries
        private final ReadExecutionController executionController;

        private int pagerMaxRemaining;
        private int counted;

        public PagersIterator(int pageSize, ConsistencyLevel consistency, ClientState clientState, ReadExecutionController executionController, long queryStartNanoTime)
        {
            this.pageSize = pageSize;
            this.consistency = consistency;
            this.clientState = clientState;
            this.executionController = executionController;
            this.queryStartNanoTime = queryStartNanoTime;
        }

        protected RowIterator computeNext()
        {
            while (result == null || !result.hasNext())
            {
                if (result != null)
                {
                    result.close();
                    counted += pagerMaxRemaining - pagers[current].maxRemaining();
                }

                // We are done if we have reached the page size or in the case of GROUP BY if the current pager
                // is not exhausted.
                boolean isDone = counted >= pageSize
                        || (result != null && limit.isGroupByLimit() && !pagers[current].isExhausted());

                // isExhausted() will sets us on the first non-exhausted pager
                if (isDone || isExhausted())
                {
                    closed = true;
                    return endOfData();
                }

                pagerMaxRemaining = pagers[current].maxRemaining();
                int toQuery = pageSize - counted;
                result = consistency == null
                       ? pagers[current].fetchPageInternal(toQuery, executionController)
                       : pagers[current].fetchPage(toQuery, consistency, clientState, queryStartNanoTime);
            }
            return result.next();
        }

        public void close()
        {
            remaining -= counted;
            if (result != null && !closed)
                result.close();
        }
    }

    public int maxRemaining()
    {
        return remaining;
    }
}