The client implement for SkyWalking BanyanDB in Java.
Create a BanyanDBClient with the server's several addresses and then use connect() to establish a connection.
// use `default` group
BanyanDBClient client = new BanyanDBClient("banyandb.svc:17912", "10.0.12.9:17912");
// to send any request, a connection to the server must be estabilished
client.connect();These addresses are either IP addresses or DNS names.
The client will try to connect to the server in a round-robin manner. The client will periodically refresh the server
addresses. The refresh interval can be configured by refreshInterval option.
Besides, you may pass a customized options while building a BanyanDBClient. Supported
options are listed below,
| Option | Description | Default |
|---|---|---|
| maxInboundMessageSize | Max inbound message size | 1024 * 1024 * 50 (~50MB) |
| deadline | Threshold of gRPC blocking query, unit is second | 30 (seconds) |
| refreshInterval | Refresh interval for the gRPC channel, unit is second | 30 (seconds) |
| resolveDNSInterval | DNS resolve interval, unit is second | 30 (minutes) |
| forceReconnectionThreshold | Threshold of force gRPC reconnection if network issue is encountered | 1 |
| forceTLS | Force use TLS for gRPC | false |
| sslTrustCAPath | SSL: Trusted CA Path |
// build a group sw_record for Stream with 2 shards and ttl equals to 3 days
Group g = Group.newBuilder().setMetadata(Metadata.newBuilder().setName("sw_record"))
.setCatalog(Catalog.CATALOG_STREAM)
.setResourceOpts(ResourceOpts.newBuilder()
.setShardNum(2)
.setSegmentInterval(
IntervalRule.newBuilder()
.setUnit(
IntervalRule.Unit.UNIT_DAY)
.setNum(
1))
.setTtl(
IntervalRule.newBuilder()
.setUnit(
IntervalRule.Unit.UNIT_DAY)
.setNum(
3)))
.build();
client.define(g);Then we may define a stream with customized configurations.
// build a stream trace with above group
Stream s = Stream.newBuilder()
.setMetadata(Metadata.newBuilder()
.setGroup("sw_record")
.setName("trace"))
.setEntity(Entity.newBuilder().addAllTagNames(
Arrays.asList("service_id", "service_instance_id", "is_error")))
.addTagFamilies(TagFamilySpec.newBuilder()
.setName("data")
.addTags(TagSpec.newBuilder()
.setName("data_binary")
.setType(TagType.TAG_TYPE_DATA_BINARY)))
.addTagFamilies(TagFamilySpec.newBuilder()
.setName("searchable")
.addTags(TagSpec.newBuilder()
.setName("trace_id")
.setType(TagType.TAG_TYPE_STRING))
.addTags(TagSpec.newBuilder()
.setName("is_error")
.setType(TagType.TAG_TYPE_INT))
.addTags(TagSpec.newBuilder()
.setName("service_id")
.setType(TagType.TAG_TYPE_STRING)
.setIndexedOnly(true)))
.build();
client.define(s);IndexRule.Builder ir = IndexRule.newBuilder()
.setMetadata(Metadata.newBuilder()
.setGroup("sw_record")
.setName("trace_id"))
.addTags("trace_id")
.setType(IndexRule.Type.TYPE_INVERTED)
.setAnalyzer("simple");
client.define(ir.build());IndexRuleBinding.Builder irb = IndexRuleBinding.newBuilder()
.setMetadata(BanyandbCommon.Metadata.newBuilder()
.setGroup("sw_record")
.setName("trace_binding"))
.setSubject(BanyandbDatabase.Subject.newBuilder()
.setCatalog(
BanyandbCommon.Catalog.CATALOG_STREAM)
.setName("trace"))
.addAllRules(
Arrays.asList("trace_id"))
.setBeginAt(TimeUtils.buildTimestamp(ZonedDateTime.of(2024, 1, 1, 0, 0, 0, 0, ZoneOffset.UTC)))
.setExpireAt(TimeUtils.buildTimestamp(DEFAULT_EXPIRE_AT));
client.define(irb.build());For the last line in the code block, a simple API (i.e. BanyanDBClient.define(Stream)) is used to define the schema of Stream.
The same works for Measure which will be demonstrated later.
Measure can also be defined directly with BanyanDBClient,
// build a group sw_metrics for Measure with 2 shards and ttl equals to 7 days
Group g = Group.newBuilder().setMetadata(Metadata.newBuilder().setName("sw_metric"))
.setCatalog(Catalog.CATALOG_MEASURE)
.setResourceOpts(ResourceOpts.newBuilder()
.setShardNum(2)
.setSegmentInterval(
IntervalRule.newBuilder()
.setUnit(
IntervalRule.Unit.UNIT_DAY)
.setNum(
1))
.setTtl(
IntervalRule.newBuilder()
.setUnit(
IntervalRule.Unit.UNIT_DAY)
.setNum(
7)))
.build();
client.define(g);// create a new measure schema with an additional interval
// the interval is used to specify how frequently to send a data point
Measure m = Measure.newBuilder()
.setMetadata(Metadata.newBuilder()
.setGroup("sw_metric")
.setName("service_cpm_minute"))
.setInterval(Duration.ofMinutes(1).format())
.setEntity(Entity.newBuilder().addTagNames("entity_id"))
.addTagFamilies(
TagFamilySpec.newBuilder()
.setName("default")
.addTags(
TagSpec.newBuilder()
.setName("entity_id")
.setType(
TagType.TAG_TYPE_STRING))
.addTags(
TagSpec.newBuilder()
.setName("scope")
.setType(
TagType.TAG_TYPE_STRING)))
.addFields(
FieldSpec.newBuilder()
.setName("total")
.setFieldType(
FieldType.FIELD_TYPE_INT)
.setCompressionMethod(
CompressionMethod.COMPRESSION_METHOD_ZSTD)
.setEncodingMethod(
EncodingMethod.ENCODING_METHOD_GORILLA))
.addFields(
FieldSpec.newBuilder()
.setName("value")
.setFieldType(
FieldType.FIELD_TYPE_INT)
.setCompressionMethod(
CompressionMethod.COMPRESSION_METHOD_ZSTD)
.setEncodingMethod(
EncodingMethod.ENCODING_METHOD_GORILLA))
.build();
// define a measure, as we've mentioned above
client.define(m);If you want to create an index_mode Measure:
Measure m = Measure.newBuilder()
.setMetadata(Metadata.newBuilder()
.setGroup("sw_metric")
.setName("service_traffic"))
.setEntity(Entity.newBuilder().addTagNames("service_id"))
.setIndexMode(true)
.addTagFamilies(
TagFamilySpec.newBuilder()
.setName("default")
.addTags(
TagSpec.newBuilder()
.setName("service_id")
.setType(
TagType.TAG_TYPE_STRING))
.addTags(
TagSpec.newBuilder()
.setName("layer")
.setType(
TagType.TAG_TYPE_STRING)))
.build();
// define a "index_mode" measure, as we've mentioned above
client.define(m);For more APIs usage, refer to test cases and API docs.
Construct a StreamQuery instance with given time-range and other conditions.
Note: time-range is left-inclusive and right-exclusive.
For example,
// [begin, end) = [ now - 15min, now )
Instant end = Instant.now();
Instant begin = end.minus(15, ChronoUnit.MINUTES);
// with stream schema, group=default, name=sw
StreamQuery query = new StreamQuery(Lists.newArrayList("sw_record"), "trace",
new TimestampRange(begin.toEpochMilli(), end.toEpochMilli()),
// projection tags which are indexed
ImmutableSet.of("state", "start_time", "duration", "trace_id"));
// search for all states
query.and(PairQueryCondition.StringQueryCondition.eq("searchable", "trace_id" , "1a60e0846817447eac4cd498eefd3743.1.17261060724190003"));
// set order by condition
query.setOrderBy(new AbstractQuery.OrderBy(AbstractQuery.Sort.DESC));
// set projection for un-indexed tags
query.setDataProjections(ImmutableSet.of("data_binary"));
// send the query request
client.query(query);After response is returned, elements can be fetched,
StreamQueryResponse resp = client.query(query);
List<RowEntity> entities = resp.getElements();Every item RowEntity in the list contains elementId, timestamp and tag families requested.
The StreamQueryResponse, RowEntity, TagFamily and Tag (i.e. TagAndValue) forms a hierarchical structure, where
the order of the tag families and containing tags, i.e. indexes of these objects in the List, follow the order specified
in the projection condition we've used in the request.
If you want to trace the query, you can use query.enableTrace() to get the trace spans.
// enable trace
query.enableTrace();
// send the query request
client.query(query);After response is returned, trace can be extracted,
// send the query request
StreamQueryResponse resp = client.queryStreams(query);
Trace t = resp.getTrace();For Measure, it is similar to the Stream,
// [begin, end) = [ now - 15min, now )
Instant end = Instant.now();
Instant begin = end.minus(15, ChronoUnit.MINUTES);
// with stream schema, group=sw_metrics, name=service_instance_cpm_day
MeasureQuery query = new MeasureQuery(Lists.newArrayList("sw_metrics"), "service_instance_cpm_day",
new TimestampRange(begin.toEpochMilli(), end.toEpochMilli()),
ImmutableSet.of("id", "scope", "service_id"),
ImmutableSet.of("total"));
// query max "total" with group by tag "service_id"
query.maxBy("total", ImmutableSet.of("service_id"));
// use conditions
query.and(PairQueryCondition.StringQueryCondition.eq("default", "service_id", "abc"));
// send the query request
client.query(query);After response is returned, dataPoints can be extracted,
MeasureQueryResponse resp = client.query(query);
List<DataPoint> dataPointList = resp.getDataPoints();Measure API supports TopN/BottomN search. The results or (grouped-)results are
ordered by the given field,
MeasureQuery query = new MeasureQuery("sw_metrics", "service_instance_cpm_day",
new TimestampRange(begin.toEpochMilli(), end.toEpochMilli()),
ImmutableSet.of("id", "scope", "service_id"),
ImmutableSet.of("total"));
query.topN(5, "total"); // bottomNBesides, limit and offset are used to support pagination. Tag-based sort can also
be done to the final results,
query.limit(5);
query.offset(1);
query.orderBy("service_id", Sort.DESC);If you want to trace the query, you can use query.enableTrace() to get the trace spans.
// enable trace
query.enableTrace();
// send the query request
client.query(query);After response is returned, trace can be extracted,
// send the query request
MeasureQueryResponse resp = client.query(query);
Trace trace = resp.getTrace();Both StreamQuery and MeausreQuery support the criteria flag to filter data.
criteria supports logical expressions and binary condition operations.
The expression (a=1 and b = 2) or (a=4 and b=5) could use below operations to support.
query.criteria(Or.create(
And.create(
PairQueryCondition.LongQueryCondition.eq("a", 1L),
PairQueryCondition.LongQueryCondition.eq("b", 1L)),
And.create(
PairQueryCondition.LongQueryCondition.eq("a", 4L),
PairQueryCondition.LongQueryCondition.eq("b", 5L)
)
));The execution order of conditions is from the inside to outside. The deepest condition will get executed first.
The client also provides syntactic sugar for using and or or methods.
The criteria method has a higher priority, overwriting these sugar methods.
Caveat: Sugar methods CAN NOT handle nested query.
criteriais the canonical method to take such tasks as above example shows.
When filtering data matches all the conditions, the query can append several and:
query.and(PairQueryCondition.LongQueryCondition.eq("state", 1L))
.and(PairQueryCondition.StringQueryCondition.eq("service_id", serviceId))
.and(PairQueryCondition.StringQueryCondition.eq("service_instance_id", serviceInstanceId))
.and(PairQueryCondition.StringQueryCondition.match("endpoint_id", endpointId))
.and(PairQueryCondition.LongQueryCondition.ge("duration", minDuration))
.and(PairQueryCondition.LongQueryCondition.le("duration", maxDuration))When gathering all data matches any of the conditions, the query can combine a series of or:
segmentIds.forEach(id -> query.or(PairQueryCondition.LongQueryCondition.eq("segment_id", id)))Since grpc bidi streaming is used for write protocol, build a StreamBulkWriteProcessor which would handle back-pressure for you.
Adjust maxBulkSize, flushInterval, concurrency and timeout of the consumer in different scenarios to meet requirements.
// build a StreamBulkWriteProcessor from client
StreamBulkWriteProcessor streamBulkWriteProcessor = client.buildStreamWriteProcessor(maxBulkSize, flushInterval, concurrency, timeout);The StreamBulkWriteProcessor is thread-safe and thus can be used across threads.
We highly recommend you to reuse it.
The procedure of constructing StreamWrite entity must comply with the schema of the stream, e.g.
the order of tags must exactly be the same with that defined in the schema.
And the non-existing tags must be fulfilled (with NullValue) instead of compacting all non-null tag values.
StreamWrite streamWrite = client.createStreamWrite("default", "sw", segmentId, now.toEpochMilli())
.tag("data_binary", Value.binaryTagValue(byteData))
.tag("trace_id", Value.stringTagValue(traceId)) // 0
.tag("state", Value.longTagValue(state)) // 1
.tag("service_id", Value.stringTagValue(serviceId)) // 2
.tag("service_instance_id", Value.stringTagValue(serviceInstanceId)) // 3
.tag("endpoint_id", Value.stringTagValue(endpointId)) // 4
.tag("duration", Value.longTagValue(latency)) // 5
.tag("http.method", Value.stringTagValue(null)) // 6
.tag("status_code", Value.stringTagValue(httpStatusCode)) // 7
.tag("db.type", Value.stringTagValue(dbType)) // 8
.tag("db.instance", Value.stringTagValue(dbInstance)) // 9
.tag("mq.broker", Value.stringTagValue(broker)) // 10
.tag("mq.topic", Value.stringTagValue(topic)) // 11
.tag("mq.queue", Value.stringTagValue(queue)); // 12
CompletableFuture<Void> f = streamBulkWriteProcessor.add(streamWrite);
f.get(10, TimeUnit.SECONDS);The writing procedure for Measure is similar to the above described process and leverages the bidirectional streaming of gRPC,
// build a MeasureBulkWriteProcessor from client
MeasureBulkWriteProcessor measureBulkWriteProcessor = client.buildMeasureWriteProcessor(maxBulkSize, flushInterval, concurrency, timeout);A BulkWriteProcessor is created by calling buildMeasureWriteProcessor. Then build the MeasureWrite object and send with bulk processor,
Instant now = Instant.now();
MeasureWrite measureWrite = client.createMeasureWrite("sw_metric", "service_cpm_minute", now.toEpochMilli());
measureWrite.tag("id", TagAndValue.stringTagValue("1"))
.tag("entity_id", TagAndValue.stringTagValue("entity_1"))
.field("total", TagAndValue.longFieldValue(100))
.field("value", TagAndValue.longFieldValue(1));
CompletableFuture<Void> f = measureBulkWriteProcessor.add(measureWrite);
f.get(10, TimeUnit.SECONDS);Property APIs are used to store key-value pairs.
apply will always succeed whenever the property exists or not.
The old value will be overwritten if already existed, otherwise a new value will be set.
Property property = Property.create("default", "sw", "ui_template")
.addTag(TagAndValue.newStringTag("name", "hello"))
.addTag(TagAndValue.newStringTag("state", "successd"))
.build();
this.client.apply(property); //created:true tagsNum:2The operation supports updating partial tags.
Property property = Property.create("default", "sw", "ui_template")
.addTag(TagAndValue.newStringTag("state", "failed"))
.build();
this.client.apply(property); //created:false tagsNum:1The property supports setting TTL.
Property property = Property.create("default", "sw", "temp_date")
.addTag(TagAndValue.newStringTag("state", "failed"))
.ttl("30m")
.build();
this.client.apply(property); //created:false tagsNum:1 lease_id:1The property's TTL can be extended by calling Client.keepAliveProperty,
this.client.keepAliveProperty(1); //lease_id:1The property's live time is reset to 30 minutes.
Property can be queried via Client.findProperty,
Property gotProperty = this.client.findProperty("default", "sw", "ui_template");The query operation could filter tags,
Property gotProperty = this.client.findProperty("default", "sw", "ui_template", "state");Property can be deleted by calling Client.deleteProperty,
this.client.deleteProperty("default", "sw", "ui_template"); //deleted:true tagsNum:2The delete operation could remove specific tags instead of the whole property.
this.client.deleteProperty("default", "sw", "ui_template", "state"); //deleted:true tagsNum:1./mvnw clean package
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