use of com.apple.foundationdb.record.metadata.Index in project fdb-record-layer by FoundationDB.
the class IndexingScrubMissing method scrubRecordsRangeOnly.
@Nonnull
private CompletableFuture<Boolean> scrubRecordsRangeOnly(@Nonnull FDBRecordStore store, byte[] startBytes, byte[] endBytes, @Nonnull AtomicLong recordsScanned) {
// return false when done
Index index = common.getIndex();
final RecordMetaData metaData = store.getRecordMetaData();
final RecordMetaDataProvider recordMetaDataProvider = common.getRecordStoreBuilder().getMetaDataProvider();
if (recordMetaDataProvider == null || !metaData.equals(recordMetaDataProvider.getRecordMetaData())) {
throw new MetaDataException("Store does not have the same metadata");
}
final IndexMaintainer maintainer = store.getIndexMaintainer(index);
// scrubbing only readable, VALUE, idempotence indexes (at least for now)
validateOrThrowEx(maintainer.isIdempotent(), "scrubbed index is not idempotent");
validateOrThrowEx(index.getType().equals(IndexTypes.VALUE) || scrubbingPolicy.ignoreIndexTypeCheck(), "scrubbed index is not a VALUE index");
validateOrThrowEx(store.getIndexState(index) == IndexState.READABLE, "scrubbed index is not readable");
RangeSet rangeSet = new RangeSet(indexScrubRecordsRangeSubspace(store, index));
AsyncIterator<Range> ranges = rangeSet.missingRanges(store.ensureContextActive(), startBytes, endBytes).iterator();
final ExecuteProperties.Builder executeProperties = ExecuteProperties.newBuilder().setIsolationLevel(IsolationLevel.SNAPSHOT).setReturnedRowLimit(// always respectLimit in this path; +1 allows a continuation item
getLimit() + 1);
final ScanProperties scanProperties = new ScanProperties(executeProperties.build());
return ranges.onHasNext().thenCompose(hasNext -> {
if (Boolean.FALSE.equals(hasNext)) {
// Here: no more missing ranges - all done
// To avoid stale metadata, we'll keep the scrubbed-ranges indicator empty until the next scrub call.
Transaction tr = store.getContext().ensureActive();
tr.clear(indexScrubRecordsRangeSubspace(store, index).range());
return AsyncUtil.READY_FALSE;
}
final Range range = ranges.next();
final Tuple rangeStart = RangeSet.isFirstKey(range.begin) ? null : Tuple.fromBytes(range.begin);
final Tuple rangeEnd = RangeSet.isFinalKey(range.end) ? null : Tuple.fromBytes(range.end);
final TupleRange tupleRange = TupleRange.between(rangeStart, rangeEnd);
final RecordCursor<FDBStoredRecord<Message>> cursor = store.scanRecords(tupleRange, null, scanProperties);
final AtomicBoolean hasMore = new AtomicBoolean(true);
final AtomicReference<RecordCursorResult<FDBStoredRecord<Message>>> lastResult = new AtomicReference<>(RecordCursorResult.exhausted());
final long scanLimit = scrubbingPolicy.getEntriesScanLimit();
// Note that currently we only scrub idempotent indexes
final boolean isIdempotent = true;
return iterateRangeOnly(store, cursor, this::getRecordIfMissingIndex, lastResult, hasMore, recordsScanned, isIdempotent).thenApply(vignore -> hasMore.get() ? lastResult.get().get().getPrimaryKey() : rangeEnd).thenCompose(cont -> rangeSet.insertRange(store.ensureContextActive(), packOrNull(rangeStart), packOrNull(cont), true).thenApply(ignore -> {
if (scanLimit > 0) {
scanCounter += recordsScanned.get();
if (scanLimit <= scanCounter) {
return false;
}
}
return !Objects.equals(cont, rangeEnd);
}));
});
}
use of com.apple.foundationdb.record.metadata.Index in project fdb-record-layer by FoundationDB.
the class IndexingThrottle method throttledRunAsync.
@Nonnull
<R> CompletableFuture<R> throttledRunAsync(@Nonnull final Function<FDBRecordStore, CompletableFuture<R>> function, @Nonnull final BiFunction<R, Throwable, Pair<R, Throwable>> handlePostTransaction, @Nullable final BiConsumer<FDBException, List<Object>> handleLessenWork, @Nullable final List<Object> additionalLogMessageKeyValues) {
List<Object> onlineIndexerLogMessageKeyValues = new ArrayList<>(Arrays.asList(LogMessageKeys.INDEX_NAME, common.getTargetIndexesNames(), LogMessageKeys.INDEXER_ID, common.getUuid()));
if (additionalLogMessageKeyValues != null) {
onlineIndexerLogMessageKeyValues.addAll(additionalLogMessageKeyValues);
}
AtomicInteger tries = new AtomicInteger(0);
CompletableFuture<R> ret = new CompletableFuture<>();
AtomicLong toWait = new AtomicLong(common.getRunner().getDatabase().getFactory().getInitialDelayMillis());
AsyncUtil.whileTrue(() -> {
loadConfig();
return common.getRunner().runAsync(context -> common.getRecordStoreBuilder().copyBuilder().setContext(context).openAsync().thenCompose(store -> {
for (Index index : common.getTargetIndexes()) {
IndexState indexState = store.getIndexState(index);
if (indexState != expectedIndexState) {
throw new RecordCoreStorageException("Unexpected index state", LogMessageKeys.INDEX_NAME, index.getName(), common.getRecordStoreBuilder().getSubspaceProvider().logKey(), common.getRecordStoreBuilder().getSubspaceProvider().toString(context), LogMessageKeys.INDEX_STATE, indexState, LogMessageKeys.INDEX_STATE_PRECONDITION, expectedIndexState);
}
}
return function.apply(store);
}), handlePostTransaction, onlineIndexerLogMessageKeyValues).handle((value, e) -> {
if (e == null) {
ret.complete(value);
return AsyncUtil.READY_FALSE;
} else {
int currTries = tries.getAndIncrement();
FDBException fdbE = getFDBException(e);
if (currTries < common.config.getMaxRetries() && fdbE != null && lessenWorkCodes.contains(fdbE.getCode())) {
if (handleLessenWork != null) {
handleLessenWork.accept(fdbE, onlineIndexerLogMessageKeyValues);
}
long delay = (long) (Math.random() * toWait.get());
toWait.set(Math.min(toWait.get() * 2, common.getRunner().getDatabase().getFactory().getMaxDelayMillis()));
if (LOGGER.isWarnEnabled()) {
final KeyValueLogMessage message = KeyValueLogMessage.build("Retrying Runner Exception", LogMessageKeys.INDEXER_CURR_RETRY, currTries, LogMessageKeys.INDEXER_MAX_RETRIES, common.config.getMaxRetries(), LogMessageKeys.DELAY, delay, LogMessageKeys.LIMIT, limit);
message.addKeysAndValues(onlineIndexerLogMessageKeyValues);
LOGGER.warn(message.toString(), e);
}
return MoreAsyncUtil.delayedFuture(delay, TimeUnit.MILLISECONDS).thenApply(vignore3 -> true);
} else {
return completeExceptionally(ret, e, onlineIndexerLogMessageKeyValues);
}
}
}).thenCompose(Function.identity());
}, common.getRunner().getExecutor()).whenComplete((vignore, e) -> {
if (e != null) {
// Just update ret and ignore the returned future.
completeExceptionally(ret, e, onlineIndexerLogMessageKeyValues);
}
});
return ret;
}
use of com.apple.foundationdb.record.metadata.Index in project fdb-record-layer by FoundationDB.
the class TextIndexMaintainer method scan.
/**
* Scan this index between a range of tokens. This index type requires that it be scanned only
* by text token. The range to scan can otherwise be between any two entries in the list, and
* scans over a prefix are supported by passing a value of <code>range</code> that uses
* {@link com.apple.foundationdb.record.EndpointType#PREFIX_STRING PREFIX_STRING} as both endpoint types.
* The keys returned in the index entry will include the token that was found in the index
* when scanning in the column that is used for the text field of the index's root expression.
* The value portion of each index entry will be a tuple whose first element is the position
* list for that entry within its associated record's field.
*
* @param scanType the {@link IndexScanType type} of scan to perform
* @param range the range to scan
* @param continuation any continuation from a previous scan invocation
* @param scanProperties skip, limit and other properties of the scan
* @return a cursor over all index entries in <code>range</code>
* @throws RecordCoreException if <code>scanType</code> is not {@link IndexScanType#BY_TEXT_TOKEN}
* @see TextCursor
*/
@Nonnull
@Override
// not closing the returned cursor
@SuppressWarnings("squid:S2095")
public RecordCursor<IndexEntry> scan(@Nonnull IndexScanType scanType, @Nonnull TupleRange range, @Nullable byte[] continuation, @Nonnull ScanProperties scanProperties) {
if (scanType != IndexScanType.BY_TEXT_TOKEN) {
throw new RecordCoreException("Can only scan text index by text token.");
}
int textPosition = textFieldPosition(state.index.getRootExpression());
TextSubspaceSplitter subspaceSplitter = new TextSubspaceSplitter(state.indexSubspace, textPosition + 1);
Range byteRange = range.toRange();
ScanProperties withAdjustedLimit = scanProperties.with(ExecuteProperties::clearSkipAndAdjustLimit);
ExecuteProperties adjustedExecuteProperties = withAdjustedLimit.getExecuteProperties();
// Callback for updating the byte scan limit
final ByteScanLimiter byteScanLimiter = adjustedExecuteProperties.getState().getByteScanLimiter();
final Consumer<KeyValue> callback = keyValue -> byteScanLimiter.registerScannedBytes(keyValue.getKey().length + keyValue.getValue().length);
BunchedMapMultiIterator<Tuple, List<Integer>, Tuple> iterator = getBunchedMap(state.context).scanMulti(state.context.readTransaction(adjustedExecuteProperties.getIsolationLevel().isSnapshot()), state.indexSubspace, subspaceSplitter, byteRange.begin, byteRange.end, continuation, adjustedExecuteProperties.getReturnedRowLimit(), callback, scanProperties.isReverse());
RecordCursor<IndexEntry> cursor = new TextCursor(iterator, state.store.getExecutor(), state.context, withAdjustedLimit, state.index);
if (scanProperties.getExecuteProperties().getSkip() != 0) {
cursor = cursor.skip(scanProperties.getExecuteProperties().getSkip());
}
return cursor;
}
use of com.apple.foundationdb.record.metadata.Index 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.Index in project fdb-record-layer by FoundationDB.
the class SyntheticRecordPlanner method forIndex.
/**
* Construct a plan for generating synthetic records for a given index.
*
* The generated records will be of indexed record types.
*
* Used by the {@link com.apple.foundationdb.record.provider.foundationdb.OnlineIndexer} to build from a full scan of stored records.
* @param index an index on synthetic record types
* @return a plan that can be applied to scanned records to generate synthetic records
*/
@Nonnull
public SyntheticRecordFromStoredRecordPlan forIndex(@Nonnull Index index) {
final Collection<RecordType> recordTypes = recordMetaData.recordTypesForIndex(index);
if (recordTypes.size() == 1) {
final RecordType recordType = recordTypes.iterator().next();
if (!recordType.isSynthetic()) {
throw new RecordCoreException("Index does not apply to synthetic record types " + index);
}
return forType((SyntheticRecordType<?>) recordType);
}
Multimap<String, SyntheticRecordFromStoredRecordPlan> byType = ArrayListMultimap.create();
for (RecordType recordType : recordTypes) {
if (!(recordType instanceof JoinedRecordType)) {
throw unknownSyntheticType(recordType);
}
JoinedRecordType joinedRecordType = (JoinedRecordType) recordType;
Optional<JoinedRecordType.JoinConstituent> maybeConstituent = joinedRecordType.getConstituents().stream().filter(c -> !c.isOuterJoined()).findFirst();
if (maybeConstituent.isPresent()) {
addToByType(byType, joinedRecordType, maybeConstituent.get());
} else {
for (JoinedRecordType.JoinConstituent joinConstituent : joinedRecordType.getConstituents()) {
addToByType(byType, joinedRecordType, joinConstituent);
}
}
}
return createByType(byType);
}
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