Examples with RecordCursor com.apple.foundationdb.record.RecordCursor used on opensource projects

Example 6 with RecordCursor

use of com.apple.foundationdb.record.RecordCursor in project fdb-record-layer by FoundationDB.

the class Main method main.

public static void main(String[] args) {
    // Get a database connection.
    FDBDatabase fdb = FDBDatabaseFactory.instance().getDatabase();
    // Create a subspace using the key space API to create a subspace within
    // the cluster used by this record store. The key space API in general
    // allows the user to specify a hierarchical structure of named sub-paths.
    // Each record store can then fill in the named entries within the path
    // with values relevant to that store. If the key space includes a directory
    // layer directory, then the value supplied by the user will be replaced
    // by a short prefix supplied by the the directory layer. The results from
    // the directory layer are cached locally by the Record Layer to avoid excessive
    // database reads.
    // 
    // In this case, the key space implies that there are multiple "applications"
    // that might be defined to run on the same FoundationDB cluster, and then
    // each "application" might have multiple "environments". This could be used,
    // for example, to connect to either the "prod" or "qa" environment for the same
    // application from within the same code base.
    final KeySpace keySpace = new KeySpace(new DirectoryLayerDirectory("application").addSubdirectory(new KeySpaceDirectory("environment", KeySpaceDirectory.KeyType.STRING)));
    // Create a path for the "record-layer-sample" application's demo environment.
    // Clear all existing data and then return the subspace associated with the key space path.
    final KeySpacePath path = keySpace.path("application", "record-layer-sample").add("environment", "demo");
    // Clear out any data that may be in the record store.
    LOGGER.info("Clearing the Record Store ...");
    fdb.run(context -> {
        path.deleteAllData(context);
        return null;
    });
    // Build the metadata. This simple approach only works for primary
    // keys and secondary indexes defined in the Protobuf message types.
    RecordMetaData rmd = RecordMetaData.build(SampleProto.getDescriptor());
    FDBRecordStore.Builder recordStoreBuilder = FDBRecordStore.newBuilder().setMetaDataProvider(rmd).setKeySpacePath(path);
    // Write records for Vendor and Item.
    LOGGER.info("Writing Vendor and Item record ...");
    fdb.run((FDBRecordContext cx) -> {
        FDBRecordStore store = recordStoreBuilder.copyBuilder().setContext(cx).create();
        store.saveRecord(SampleProto.Vendor.newBuilder().setVendorId(9375L).setVendorName("Acme").build());
        store.saveRecord(SampleProto.Vendor.newBuilder().setVendorId(1066L).setVendorName("Buy n Large").build());
        store.saveRecord(SampleProto.Item.newBuilder().setItemId(4836L).setItemName("GPS").setVendorId(9375L).build());
        store.saveRecord(SampleProto.Item.newBuilder().setItemId(9970L).setItemName("Personal Transport").setVendorId(1066L).build());
        store.saveRecord(SampleProto.Item.newBuilder().setItemId(8380L).setItemName("Piles of Garbage").setVendorId(1066L).build());
        return null;
    });
    // Use the primary key declared in the Vendor message type to read a
    // record.
    LOGGER.info("Reading Vendor record with primary key 9375L ...");
    SampleProto.Vendor.Builder readBuilder = fdb.run((FDBRecordContext cx) -> {
        FDBRecordStore store = recordStoreBuilder.copyBuilder().setContext(cx).open();
        return SampleProto.Vendor.newBuilder().mergeFrom(store.loadRecord(Key.Evaluated.scalar(9375L).toTuple()).getRecord());
    });
    LOGGER.info("    Result -> Id: {}, Name: {}", readBuilder.getVendorId(), readBuilder.getVendorName());
    // Using the secondary index declared in the message type, query
    // Item by vendor ID, then look up the item ID.
    LOGGER.info("Looking for item IDs with vendor ID 9375L ...");
    ArrayList<Long> ids = fdb.run((FDBRecordContext cx) -> {
        ArrayList<Long> itemIDs = new ArrayList<>();
        FDBRecordStore store = recordStoreBuilder.copyBuilder().setContext(cx).open();
        RecordQuery query = RecordQuery.newBuilder().setRecordType("Item").setFilter(Query.field("vendor_id").equalsValue(9375L)).build();
        try (RecordCursor<FDBQueriedRecord<Message>> cursor = store.executeQuery(query)) {
            RecordCursorResult<FDBQueriedRecord<Message>> result;
            do {
                result = cursor.getNext();
                if (result.hasNext()) {
                    itemIDs.add(SampleProto.Item.newBuilder().mergeFrom(result.get().getRecord()).getItemId());
                }
            } while (result.hasNext());
        }
        return itemIDs;
    });
    ids.forEach((Long res) -> LOGGER.info("    Result -> Vendor ID: 9375, Item ID: {}", res));
    // A kind of hand-crafted "cross-table join" (in some sense). This returns a list
    // linking the name of each vendor to the names of the products they sell.
    // Note that this query is entirely non-blocking until the end.
    // In SQL, this might look something like:
    // 
    // SELECT Vendor.name, Item.name FROM Item JOIN Vendor ON Vendor.vendor_id = Item.vid
    // 
    // One difference is that the above SQL query will flatten the results out so that there
    // is exactly one returned row per item name (per vendor) where as the map returned by
    // this RecordLayer query will feature exactly one entry per vendor where the key is the
    // vendor name and the value is the vendor's items.
    // 
    // Note that this query is not particularly efficient as is. To make this efficient, one
    // might consider an index on vendor name. This could scan the index to get the vendor
    // name of the Vendor record type and a second index on item by vendor ID, perhaps with
    // the item name in the value portion of the index definition. This would allow the
    // query to be satisfied with one scan of the vendor name index and another scan of the
    // item's vendor ID index (one scan per vendor).
    LOGGER.info("Grouping items by vendor ...");
    Map<String, List<String>> namesToItems = fdb.run((FDBRecordContext cx) -> cx.asyncToSync(FDBStoreTimer.Waits.WAIT_EXECUTE_QUERY, recordStoreBuilder.copyBuilder().setContext(cx).openAsync().thenCompose(store -> {
        // Outer plan gets all of the vendors
        RecordQueryPlan outerPlan = store.planQuery(RecordQuery.newBuilder().setRecordType("Vendor").setRequiredResults(Arrays.asList(field("vendor_id"), field("vendor_name"))).build());
        // Inner plan gets all items for the given vendor ID.
        // Using "equalsParameter" does the plan once and re-uses the plan for each vendor ID.
        RecordQueryPlan innerPlan = store.planQuery(RecordQuery.newBuilder().setRecordType("Item").setRequiredResults(Collections.singletonList(field("item_name"))).setFilter(Query.field("vendor_id").equalsParameter("vid")).build());
        return store.executeQuery(outerPlan).mapPipelined(record -> {
            SampleProto.Vendor vendor = SampleProto.Vendor.newBuilder().mergeFrom(record.getRecord()).build();
            return innerPlan.execute(store, EvaluationContext.forBinding("vid", vendor.getVendorId())).map(innerRecord -> SampleProto.Item.newBuilder().mergeFrom(innerRecord.getRecord()).getItemName()).asList().thenApply(list -> Pair.of(vendor.getVendorName(), list));
        }, 10).asList().thenApply((List<Pair<String, List<String>>> list) -> list.stream().collect(Collectors.toMap(Pair::getKey, Pair::getValue)));
    })));
    namesToItems.forEach((String name, List<String> items) -> LOGGER.info("    Result -> Vendor Name: {}, Item names: {}", name, items));
    // Richer indexes:
    // To build richer primary keys or secondary indexes (than those definable in the protobuf
    // message types), you need to use the more verbose and powerful RecordMetaDataBuilder.
    RecordMetaDataBuilder rmdBuilder = RecordMetaData.newBuilder().setRecords(SampleProto.getDescriptor());
    // Order customers by last name, then first name, then their ID if otherwise equal.
    // NOTE: This operation is dangerous if you have existing data! Existing records are *not*
    // automatically migrated.
    rmdBuilder.getRecordType("Customer").setPrimaryKey(concatenateFields("last_name", "first_name", "customer_id"));
    // Add a global count index. Most record stores should probably add this index as it allows
    // the database to make intelligent decisions based on the current size of the record store.
    rmdBuilder.addUniversalIndex(new Index("globalCount", new GroupingKeyExpression(EmptyKeyExpression.EMPTY, 0), IndexTypes.COUNT));
    // Add a FanType.FanOut secondary index for email_address, so that
    // each value for email_address generates its own key in the index.
    rmdBuilder.addIndex("Customer", new Index("email_address", field("email_address", FanType.FanOut), IndexTypes.VALUE));
    // Add a FanType.Concatenate secondary index for preference_tag, so
    // that all values for preference_tag generate a single key in the index.
    rmdBuilder.addIndex("Customer", new Index("preference_tag", field("preference_tag", FanType.Concatenate), IndexTypes.VALUE));
    // Add an index on the count of each preference tag. This allows us to
    // quickly get the number of users for each preference tag. The key
    // provided will create a separate "count" field for each value of the
    // preference_tag field and keep track of the number of customer
    // records with each value.
    rmdBuilder.addIndex("Customer", new Index("preference_tag_count", new GroupingKeyExpression(field("preference_tag", FanType.FanOut), 0), IndexTypes.COUNT));
    // Add a nested secondary index for order such that each value for
    // quantity in Order generates a single key in the index.
    rmdBuilder.addIndex("Customer", new Index("order", field("order", FanType.FanOut).nest("quantity"), IndexTypes.VALUE));
    // Add an index on the sum of the quantity of each item in each
    // order. This can be used to know how many of each item have been ordered across
    // all customers. The grouping key here is a little hairy, but it
    // specifies that the "item_id" column should be used as a grouping key
    // and the quantity used as the sum value, so it will keep track of the
    // quantity ordered of each item.
    rmdBuilder.addIndex("Customer", new Index("item_quantity_sum", new GroupingKeyExpression(field("order", FanType.FanOut).nest(concatenateFields("item_id", "quantity")), 1), IndexTypes.SUM));
    // Rebuild the metadata for the newly added indexes before reading or
    // writing more data.
    RecordMetaData rmd2 = rmdBuilder.getRecordMetaData();
    recordStoreBuilder.setMetaDataProvider(rmd2);
    // Calling "open" on an existing record store with new meta-data will
    // create the index and place them in a "disabled" mode that means that
    // they cannot yet be used for queries. (In particular, the query planner
    // will ignore this index and any attempt to read from the index will
    // throw an error.) To enable querying, one must invoke the online index
    // builder. This will scan through the record store across multiple
    // transactions and populate the new indexes with data from the existing
    // entries. During the build job, the record store remains available for
    // reading and writing, but there may be additional conflicts if the index
    // build job and normal operations happen to mutate the same records.
    RecordStoreState storeState = fdb.run(cx -> {
        FDBRecordStore store = recordStoreBuilder.copyBuilder().setContext(cx).open();
        return store.getRecordStoreState();
    });
    LOGGER.info("Running index builds of new indexes:");
    // Build all of the indexes in parallel by firing off a future for each and
    // then wait for all of them.
    fdb.asyncToSync(null, FDBStoreTimer.Waits.WAIT_ONLINE_BUILD_INDEX, AsyncUtil.whenAll(storeState.getDisabledIndexNames().stream().map(indexName -> {
        // Build this index. It will begin the background job and return a future
        // that will complete when the index is ready for querying.
        OnlineIndexer indexBuilder = OnlineIndexer.newBuilder().setDatabase(fdb).setRecordStoreBuilder(recordStoreBuilder).setIndex(indexName).build();
        return indexBuilder.buildIndexAsync().thenRun(() -> LOGGER.info("  Index build of {} is complete.", indexName)).whenComplete((vignore, eignore) -> indexBuilder.close());
    }).collect(Collectors.toList())));
    // Write larger records for Customer (and Order).
    LOGGER.info("Adding records with new secondary indexes ...");
    fdb.run((FDBRecordContext cx) -> {
        FDBRecordStore store = recordStoreBuilder.copyBuilder().setContext(cx).open();
        store.saveRecord(SampleProto.Customer.newBuilder().setCustomerId(9264L).setFirstName("John").setLastName("Smith").addEmailAddress("jsmith@example.com").addEmailAddress("john_smith@example.com").addPreferenceTag("books").addPreferenceTag("movies").addOrder(SampleProto.Order.newBuilder().setOrderId(3875L).setItemId(9374L).setQuantity(2)).addOrder(SampleProto.Order.newBuilder().setOrderId(4828L).setItemId(2740L).setQuantity(1)).setPhoneNumber("(703) 555-8255").build());
        store.saveRecord(SampleProto.Customer.newBuilder().setCustomerId(8365L).setFirstName("Jane").setLastName("Doe").addEmailAddress("jdoe@example.com").addEmailAddress("jane_doe@example.com").addPreferenceTag("games").addPreferenceTag("lawn").addPreferenceTag("books").addOrder(SampleProto.Order.newBuilder().setOrderId(9280L).setItemId(2740L).setQuantity(3)).setPhoneNumber("(408) 555-0248").build());
        return null;
    });
    // Get the record count. This uses the global count index to get the
    // full number of records in the store.
    Long recordCount = fdb.run((FDBRecordContext cx) -> cx.asyncToSync(FDBStoreTimer.Waits.WAIT_EXECUTE_QUERY, recordStoreBuilder.copyBuilder().setContext(cx).openAsync().thenCompose(FDBRecordStore::getSnapshotRecordCount)));
    LOGGER.info("Store contains {} records.", recordCount);
    // Query all records with the first name "Jane".
    // Performs a full scan of the primary key index.
    LOGGER.info("Retrieving all customers with first name \"Jane\"...");
    List<String> names = fdb.run((FDBRecordContext cx) -> {
        RecordQuery query = RecordQuery.newBuilder().setRecordType("Customer").setFilter(Query.field("first_name").equalsValue("Jane")).build();
        return readNames(recordStoreBuilder, cx, query);
    });
    names.forEach((String res) -> LOGGER.info("    Result -> {}", res));
    // Query all records with last name "Doe".
    // Scans only the customers from the primary key index.
    LOGGER.info("Retrieving all customers with last name \"Doe\"...");
    names = fdb.run((FDBRecordContext cx) -> {
        RecordQuery query = RecordQuery.newBuilder().setRecordType("Customer").setFilter(Query.field("last_name").equalsValue("Doe")).build();
        return readNames(recordStoreBuilder, cx, query);
    });
    names.forEach((String res) -> LOGGER.info("    Result -> {}", res));
    // Query all records with first_name "Jane" and last_name "Doe"
    // Scans only the customers from the primary key index.
    LOGGER.info("Retrieving all customers with name \"Jane Doe\"...");
    names = fdb.run((FDBRecordContext cx) -> {
        RecordQuery query = RecordQuery.newBuilder().setRecordType("Customer").setFilter(Query.and(Query.field("first_name").equalsValue("Jane"), Query.field("last_name").equalsValue("Doe"))).build();
        return readNames(recordStoreBuilder, cx, query);
    });
    names.forEach((String res) -> LOGGER.info("    Result -> {}", res));
    // Query all records with an email address beginning with "john".
    // Uses FanType.FanOut secondary index.
    LOGGER.info("Retrieving all customers with an email address beginning with \"john\"...");
    Map<String, List<String>> addresses = fdb.run((FDBRecordContext cx) -> {
        RecordQuery query = RecordQuery.newBuilder().setRecordType("Customer").setFilter(Query.field("email_address").oneOfThem().startsWith("john")).build();
        return cx.asyncToSync(FDBStoreTimer.Waits.WAIT_EXECUTE_QUERY, recordStoreBuilder.copyBuilder().setContext(cx).openAsync().thenCompose(store -> {
            Map<String, List<String>> addressMap = new HashMap<>();
            return store.executeQuery(query).forEach((FDBQueriedRecord<Message> record) -> {
                SampleProto.Customer.Builder builder = SampleProto.Customer.newBuilder().mergeFrom(record.getRecord());
                addressMap.put(builder.getFirstName() + " " + builder.getLastName(), builder.getEmailAddressList());
            }).thenApply(v -> addressMap);
        }));
    });
    addresses.forEach((String k, List<String> vals) -> LOGGER.info("    Result -> {} with emails {}", k, vals));
    // Query all records with preference_tags "books" and "movies".
    // Uses FanType.Concatenate secondary index.
    LOGGER.info("Retrieving all customers with preference tags \"books\" and \"movies\"...");
    names = fdb.run((FDBRecordContext cx) -> {
        RecordQuery query = RecordQuery.newBuilder().setRecordType("Customer").setFilter(Query.and(Query.field("preference_tag").oneOfThem().equalsValue("books"), Query.field("preference_tag").oneOfThem().equalsValue("movies"))).build();
        return readNames(recordStoreBuilder, cx, query);
    });
    names.forEach((String res) -> LOGGER.info("    Result -> {}", res));
    // Get the number of customers who have "books" listed as one of their preference tags
    Long bookPreferenceCount = fdb.run((FDBRecordContext cx) -> cx.asyncToSync(FDBStoreTimer.Waits.WAIT_EXECUTE_QUERY, recordStoreBuilder.copyBuilder().setContext(cx).openAsync().thenCompose(store -> {
        Index index = store.getRecordMetaData().getIndex("preference_tag_count");
        IndexAggregateFunction function = new IndexAggregateFunction(FunctionNames.COUNT, index.getRootExpression(), index.getName());
        return store.evaluateAggregateFunction(Collections.singletonList("Customer"), function, Key.Evaluated.scalar("books"), IsolationLevel.SERIALIZABLE).thenApply(tuple -> tuple.getLong(0));
    })));
    LOGGER.info("Number of customers with the \"books\" preference tag: {}", bookPreferenceCount);
    // Query all customers with an order of quantity greater than 2.
    // Uses nested secondary index.
    LOGGER.info("Retrieving all customers with an order of quantity greater than 2 ...");
    names = fdb.run((FDBRecordContext cx) -> {
        RecordQuery query = RecordQuery.newBuilder().setRecordType("Customer").setFilter(Query.field("order").oneOfThem().matches(Query.field("quantity").greaterThan(2))).build();
        return readNames(recordStoreBuilder, cx, query);
    });
    names.forEach((String res) -> LOGGER.info("    Result -> {}", res));
    // Get the sum of the quantity of items ordered for item ID 2740.
    // Using the index, it can determine this by reading a single
    // key in the database.
    Long itemQuantitySum = fdb.run((FDBRecordContext cx) -> cx.asyncToSync(FDBStoreTimer.Waits.WAIT_EXECUTE_QUERY, recordStoreBuilder.copyBuilder().setContext(cx).openAsync().thenCompose(store -> {
        Index index = store.getRecordMetaData().getIndex("item_quantity_sum");
        IndexAggregateFunction function = new IndexAggregateFunction(FunctionNames.SUM, index.getRootExpression(), index.getName());
        return store.evaluateAggregateFunction(Collections.singletonList("Customer"), function, Key.Evaluated.scalar(2740L), IsolationLevel.SERIALIZABLE).thenApply(tuple -> tuple.getLong(0));
    })));
    LOGGER.info("Total quantity ordered of item 2740L: {}", itemQuantitySum);
    // Get the sum of the quantity of all items ordered.
    // Using the index, it will do a scan that will hit one key
    // for each unique item id with a single range scan.
    Long allItemsQuantitySum = fdb.run((FDBRecordContext cx) -> cx.asyncToSync(FDBStoreTimer.Waits.WAIT_EXECUTE_QUERY, recordStoreBuilder.copyBuilder().setContext(cx).openAsync().thenCompose(store -> {
        Index index = store.getRecordMetaData().getIndex("item_quantity_sum");
        IndexAggregateFunction function = new IndexAggregateFunction(FunctionNames.SUM, index.getRootExpression(), index.getName());
        return store.evaluateAggregateFunction(Collections.singletonList("Customer"), function, TupleRange.ALL, IsolationLevel.SERIALIZABLE).thenApply(tuple -> tuple.getLong(0));
    })));
    LOGGER.info("Total quantity ordered of all items: {}", allItemsQuantitySum);
}

Example 7 with RecordCursor

use of com.apple.foundationdb.record.RecordCursor in project fdb-record-layer by FoundationDB.

the class FDBRecordStore method addRebuildRecordCountsJob.

public void addRebuildRecordCountsJob(List<CompletableFuture<Void>> work) {
    final KeyExpression recordCountKey = getRecordMetaData().getRecordCountKey();
    if (recordCountKey == null) {
        return;
    }
    if (LOGGER.isDebugEnabled()) {
        LOGGER.debug(KeyValueLogMessage.of("recounting all records", subspaceProvider.logKey(), subspaceProvider.toString(context)));
    }
    final Map<Key.Evaluated, Long> counts = new HashMap<>();
    final RecordCursor<FDBStoredRecord<Message>> records = scanRecords(null, ScanProperties.FORWARD_SCAN);
    CompletableFuture<Void> future = records.forEach(rec -> {
        Key.Evaluated subkey = recordCountKey.evaluateSingleton(rec);
        counts.compute(subkey, (k, v) -> (v == null) ? 1 : v + 1);
    }).thenApply(vignore -> {
        final Transaction tr = ensureContextActive();
        final byte[] bytes = new byte[8];
        final ByteBuffer buf = ByteBuffer.wrap(bytes).order(ByteOrder.LITTLE_ENDIAN);
        for (Map.Entry<Key.Evaluated, Long> entry : counts.entrySet()) {
            buf.putLong(entry.getValue());
            tr.set(getSubspace().pack(Tuple.from(RECORD_COUNT_KEY).addAll(entry.getKey().toTupleAppropriateList())), bytes);
            buf.clear();
        }
        return null;
    });
    future = context.instrument(FDBStoreTimer.Events.RECOUNT_RECORDS, future);
    work.add(future);
}

Example 8 with RecordCursor

use of com.apple.foundationdb.record.RecordCursor in project fdb-record-layer by FoundationDB.

the class FDBRecordStore method getPrimaryKeyBoundaries.

/**
 * Return a cursor of boundaries separating the key ranges maintained by each FDB server. This information can be
 * useful for splitting a large task (e.g., rebuilding an index for a large record store) into smaller tasks (e.g.,
 * rebuilding the index for records in certain primary key ranges) more evenly so that they can be executed in a
 * parallel fashion efficiently. The returned boundaries are an estimate from FDB's locality API and may not
 * represent the exact boundary locations at any database version.
 * <p>
 * The boundaries are returned as a cursor which is sorted and does not contain any duplicates. The first element of
 * the list is greater than or equal to <code>low</code>, and the last element is less than or equal to
 * <code>high</code>.
 * <p>
 * This implementation may not work when there are too many shard boundaries to complete in a single transaction.
 * <p>
 * Note: the returned cursor is blocking and must not be used in an asynchronous context
 *
 * @param low low endpoint of primary key range (inclusive)
 * @param high high endpoint of primary key range (exclusive)
 * @return the list of boundary primary keys
 */
@API(API.Status.EXPERIMENTAL)
@Nonnull
public RecordCursor<Tuple> getPrimaryKeyBoundaries(@Nonnull Tuple low, @Nonnull Tuple high) {
    final Transaction transaction = ensureContextActive();
    byte[] rangeStart = recordsSubspace().pack(low);
    byte[] rangeEnd = recordsSubspace().pack(high);
    CloseableAsyncIterator<byte[]> cursor = context.getDatabase().getLocalityProvider().getBoundaryKeys(transaction, rangeStart, rangeEnd);
    final boolean hasSplitRecordSuffix = hasSplitRecordSuffix();
    DistinctFilterCursorClosure closure = new DistinctFilterCursorClosure();
    return RecordCursor.flatMapPipelined(ignore -> RecordCursor.fromIterator(getExecutor(), cursor), (result, ignore) -> RecordCursor.fromIterator(getExecutor(), transaction.snapshot().getRange(result, rangeEnd, 1).iterator()), null, DEFAULT_PIPELINE_SIZE).map(keyValue -> {
        Tuple recordKey = recordsSubspace().unpack(keyValue.getKey());
        return hasSplitRecordSuffix ? recordKey.popBack() : recordKey;
    }).filter(closure::pred);
}

Example 9 with RecordCursor

use of com.apple.foundationdb.record.RecordCursor in project fdb-record-layer by FoundationDB.

the class TimeWindowLeaderboardIndexMaintainer method scan.

@Nonnull
@Override
public RecordCursor<IndexEntry> scan(@Nonnull IndexScanBounds scanBounds, @Nullable byte[] continuation, @Nonnull ScanProperties scanProperties) {
    final IndexScanType scanType = scanBounds.getScanType();
    if (scanType != IndexScanType.BY_VALUE && scanType != IndexScanType.BY_RANK && scanType != IndexScanType.BY_TIME_WINDOW) {
        throw new RecordCoreException("Can only scan leaderboard index by time window, rank or value.");
    }
    // Decode range arguments.
    final int type;
    final long timestamp;
    final TupleRange leaderboardRange;
    if (scanType == IndexScanType.BY_TIME_WINDOW) {
        // Get oldest leaderboard of type containing timestamp.
        if (scanBounds instanceof TimeWindowScanRange) {
            TimeWindowScanRange scanRange = (TimeWindowScanRange) scanBounds;
            type = scanRange.getLeaderboardType();
            timestamp = scanRange.getLeaderboardTimestamp();
            leaderboardRange = scanRange.getScanRange();
        } else {
            // TODO: For compatibility, accept scan with BY_TIME_WINDOW and TupleRange for a while.
            // This code can be removed when we are confident all callers have been converted.
            IndexScanRange scanRange = (IndexScanRange) scanBounds;
            TupleRange rankRange = scanRange.getScanRange();
            final Tuple lowRank = rankRange.getLow();
            final Tuple highRank = rankRange.getHigh();
            type = (int) lowRank.getLong(0);
            timestamp = lowRank.getLong(1);
            leaderboardRange = new TupleRange(Tuple.fromList(lowRank.getItems().subList(2, lowRank.size())), Tuple.fromList(highRank.getItems().subList(2, highRank.size())), rankRange.getLowEndpoint(), rankRange.getHighEndpoint());
        }
    } else {
        // Get the all-time leaderboard for unqualified rank or value.
        IndexScanRange scanRange = (IndexScanRange) scanBounds;
        type = TimeWindowLeaderboard.ALL_TIME_LEADERBOARD_TYPE;
        // Any value would do.
        timestamp = 0;
        leaderboardRange = scanRange.getScanRange();
    }
    final int groupPrefixSize = getGroupingCount();
    final CompletableFuture<TimeWindowLeaderboard> leaderboardFuture = oldestLeaderboardMatching(type, timestamp);
    final CompletableFuture<TupleRange> scoreRangeFuture;
    if (scanType == IndexScanType.BY_VALUE) {
        scoreRangeFuture = leaderboardFuture.thenApply(leaderboard -> leaderboard == null ? null : leaderboardRange);
    } else {
        scoreRangeFuture = leaderboardFuture.thenCompose(leaderboard -> {
            if (leaderboard == null) {
                return CompletableFuture.completedFuture(null);
            }
            final Subspace extraSubspace = getSecondarySubspace();
            final Subspace leaderboardSubspace = extraSubspace.subspace(leaderboard.getSubspaceKey());
            final RankedSet.Config leaderboardConfig = config.toBuilder().setNLevels(leaderboard.getNLevels()).build();
            return RankedSetIndexHelper.rankRangeToScoreRange(state, groupPrefixSize, leaderboardSubspace, leaderboardConfig, leaderboardRange);
        });
    }
    // Add leaderboard's key to the front and take it off of the results.
    return RecordCursor.flatMapPipelined(ignore -> RecordCursor.fromFuture(getExecutor(), scoreRangeFuture), (scoreRange, ignore) -> {
        if (scoreRange == null) {
            return RecordCursor.empty(getExecutor());
        }
        // Already waited in scoreRangeFuture.
        final TimeWindowLeaderboard leaderboard = state.context.joinNow(leaderboardFuture);
        final CompletableFuture<Boolean> highStoreFirstFuture;
        if (scanType == IndexScanType.BY_VALUE) {
            final Tuple lowGroup = scoreRange.getLow() != null && scoreRange.getLow().size() > groupPrefixSize ? TupleHelpers.subTuple(scoreRange.getLow(), 0, groupPrefixSize) : null;
            final Tuple highGroup = scoreRange.getHigh() != null && scoreRange.getHigh().size() > groupPrefixSize ? TupleHelpers.subTuple(scoreRange.getHigh(), 0, groupPrefixSize) : null;
            if (lowGroup != null && lowGroup.equals(highGroup)) {
                highStoreFirstFuture = isHighScoreFirst(leaderboard.getDirectory(), lowGroup);
            } else {
                highStoreFirstFuture = CompletableFuture.completedFuture(leaderboard.getDirectory().isHighScoreFirst());
            }
        } else {
            highStoreFirstFuture = AsyncUtil.READY_FALSE;
        }
        if (highStoreFirstFuture.isDone()) {
            return scanLeaderboard(leaderboard, state.context.joinNow(highStoreFirstFuture), scoreRange, continuation, scanProperties);
        } else {
            return RecordCursor.flatMapPipelined(ignore2 -> RecordCursor.fromFuture(getExecutor(), highStoreFirstFuture), (highScoreFirst, ignore2) -> scanLeaderboard(leaderboard, highScoreFirst, scoreRange, continuation, scanProperties), null, 1);
        }
    }, null, 1).mapPipelined(kv -> getIndexEntry(kv, groupPrefixSize, state.context.joinNow(leaderboardFuture).getDirectory()), 1);
}

Example 10 with RecordCursor

use of com.apple.foundationdb.record.RecordCursor in project fdb-record-layer by FoundationDB.

the class KeySpaceDirectory method listSubdirectoryAsync.

@Nonnull
// SonarQube doesn't realize that the cursor is wrapped and returned
@SuppressWarnings("squid:S2095")
protected RecordCursor<ResolvedKeySpacePath> listSubdirectoryAsync(@Nullable KeySpacePath listFrom, @Nonnull FDBRecordContext context, @Nonnull String subdirName, @Nullable ValueRange<?> valueRange, @Nullable byte[] continuation, @Nonnull ScanProperties scanProperties) {
    if (listFrom != null && listFrom.getDirectory() != this) {
        throw new RecordCoreException("Provided path does not belong to this directory").addLogInfo("path", listFrom, "directory", this.getName());
    }
    final KeySpaceDirectory subdir = getSubdirectory(subdirName);
    final CompletableFuture<ResolvedKeySpacePath> resolvedFromFuture = listFrom == null ? CompletableFuture.completedFuture(null) : listFrom.toResolvedPathAsync(context);
    // The chained cursor cannot implement reverse scan, so we implement it by having the
    // inner key value cursor do the reversing but telling the chained cursor we are moving
    // forward.
    final ScanProperties chainedCursorScanProperties;
    if (scanProperties.isReverse()) {
        chainedCursorScanProperties = scanProperties.setReverse(false);
    } else {
        chainedCursorScanProperties = scanProperties;
    }
    // For the read of the individual row keys, we only want to read a single key. In addition,
    // the ChainedCursor is going to do counting of our reads to apply any limits that were specified
    // on the ScanProperties.  We don't want the inner KeyValueCursor in nextTuple() to ALSO count those
    // same reads so we clear out its limits.
    final ScanProperties keyReadScanProperties = scanProperties.with(props -> props.clearState().setReturnedRowLimit(1));
    return new LazyCursor<>(resolvedFromFuture.thenCompose(resolvedFrom -> {
        final Subspace subspace = resolvedFrom == null ? new Subspace() : resolvedFrom.toSubspace();
        return subdir.getValueRange(context, valueRange, subspace).thenApply(range -> {
            final RecordCursor<Tuple> cursor = new ChainedCursor<>(context, lastKey -> nextTuple(context, subspace, range, lastKey, keyReadScanProperties), Tuple::pack, Tuple::fromBytes, continuation, chainedCursorScanProperties);
            return cursor.mapPipelined(tuple -> {
                final Tuple key = Tuple.fromList(tuple.getItems());
                return findChildForKey(context, resolvedFrom, key, 1, 0);
            }, 1);
        });
    }), context.getExecutor());
}