use of com.apple.foundationdb.record.metadata.Key in project fdb-record-layer by FoundationDB.
the class StandardIndexMaintainer method evaluateIndex.
/**
* Apply the key and value expressions to a <code>record</code>.
* @param <M> the message type of the record
* @param record the record from which the index will extract its key and value
* @return a list of index keys and values
*/
@Override
public <M extends Message> List<IndexEntry> evaluateIndex(@Nonnull FDBRecord<M> record) {
final KeyExpression rootExpression = state.index.getRootExpression();
final List<Key.Evaluated> indexKeys = rootExpression.evaluate(record);
// so we have to tease them apart.
if (rootExpression instanceof KeyWithValueExpression) {
final KeyWithValueExpression keyWithValueExpression = (KeyWithValueExpression) rootExpression;
return indexKeys.stream().map(key -> new IndexEntry(state.index, keyWithValueExpression.getKey(key), keyWithValueExpression.getValue(key))).collect(Collectors.toList());
}
return indexKeys.stream().map(key -> new IndexEntry(state.index, key)).collect(Collectors.toList());
}
use of com.apple.foundationdb.record.metadata.Key in project fdb-record-layer by FoundationDB.
the class RankIndexMaintainer method updateIndexKeys.
@Override
protected <M extends Message> CompletableFuture<Void> updateIndexKeys(@Nonnull final FDBIndexableRecord<M> savedRecord, final boolean remove, @Nonnull final List<IndexEntry> indexEntries) {
final int groupPrefixSize = getGroupingCount();
final Subspace extraSubspace = getSecondarySubspace();
final List<CompletableFuture<Void>> ordinaryIndexFutures = new ArrayList<>(indexEntries.size());
final Map<Subspace, CompletableFuture<Void>> rankFutures = Maps.newHashMapWithExpectedSize(indexEntries.size());
for (IndexEntry indexEntry : indexEntries) {
// Maintain an ordinary B-tree index by score.
CompletableFuture<Void> updateOrdinaryIndex = updateOneKeyAsync(savedRecord, remove, indexEntry);
if (!MoreAsyncUtil.isCompletedNormally(updateOrdinaryIndex)) {
ordinaryIndexFutures.add(updateOrdinaryIndex);
}
final Subspace rankSubspace;
final Tuple scoreKey;
if (groupPrefixSize > 0) {
final List<Object> keyValues = indexEntry.getKey().getItems();
rankSubspace = extraSubspace.subspace(Tuple.fromList(keyValues.subList(0, groupPrefixSize)));
scoreKey = Tuple.fromList(keyValues.subList(groupPrefixSize, keyValues.size()));
} else {
rankSubspace = extraSubspace;
scoreKey = indexEntry.getKey();
}
// It is unsafe to have two concurrent updates to the same ranked set, so ensure that at most
// one update per grouping key is ongoing at any given time
final Function<Void, CompletableFuture<Void>> futureSupplier = vignore -> RankedSetIndexHelper.updateRankedSet(state, rankSubspace, config, indexEntry.getKey(), scoreKey, remove);
CompletableFuture<Void> existingFuture = rankFutures.get(rankSubspace);
if (existingFuture == null) {
rankFutures.put(rankSubspace, futureSupplier.apply(null));
} else {
rankFutures.put(rankSubspace, existingFuture.thenCompose(futureSupplier));
}
}
return CompletableFuture.allOf(AsyncUtil.whenAll(ordinaryIndexFutures), AsyncUtil.whenAll(rankFutures.values()));
}
use of com.apple.foundationdb.record.metadata.Key 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);
}
use of com.apple.foundationdb.record.metadata.Key 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);
}
use of com.apple.foundationdb.record.metadata.Key in project fdb-record-layer by FoundationDB.
the class FDBRecordStore method getSnapshotRecordCount.
@Override
public CompletableFuture<Long> getSnapshotRecordCount(@Nonnull KeyExpression key, @Nonnull Key.Evaluated value, @Nonnull IndexQueryabilityFilter indexQueryabilityFilter) {
if (getRecordMetaData().getRecordCountKey() != null) {
if (key.getColumnSize() != value.size()) {
throw recordCoreException("key and value are not the same size");
}
final ReadTransaction tr = context.readTransaction(true);
final Tuple subkey = Tuple.from(RECORD_COUNT_KEY).addAll(value.toTupleAppropriateList());
if (getRecordMetaData().getRecordCountKey().equals(key)) {
return tr.get(getSubspace().pack(subkey)).thenApply(FDBRecordStore::decodeRecordCount);
} else if (key.isPrefixKey(getRecordMetaData().getRecordCountKey())) {
AsyncIterable<KeyValue> kvs = tr.getRange(getSubspace().range(Tuple.from(RECORD_COUNT_KEY)));
return MoreAsyncUtil.reduce(getExecutor(), kvs.iterator(), 0L, (count, kv) -> count + decodeRecordCount(kv.getValue()));
}
}
return evaluateAggregateFunction(Collections.emptyList(), IndexFunctionHelper.count(key), TupleRange.allOf(value.toTuple()), IsolationLevel.SNAPSHOT, indexQueryabilityFilter).thenApply(tuple -> tuple.getLong(0));
}
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