Package io.deephaven.kafka

Class KafkaTools

java.lang.Object

io.deephaven.kafka.KafkaTools

public class KafkaTools
extends Object

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	KafkaTools.Consume
static interface	KafkaTools.ConsumerLoopCallback	A callback which is invoked from the consumer loop, enabling clients to inject logic to be invoked by the Kafka consumer thread.
static interface	KafkaTools.InitialOffsetLookup	Determines the initial offset to seek to for a given KafkaConsumer and TopicPartition.
static enum	KafkaTools.KeyOrValue	Enum to specify operations that may apply to either of Kafka KEY or VALUE fields.
static class	KafkaTools.KeyOrValueIngestData
static interface	KafkaTools.PerPartitionConsumerRegistrar
static class	KafkaTools.Produce
static interface	KafkaTools.SingleConsumerRegistrar
static interface	KafkaTools.StreamConsumerRegistrarProvider	Marker interface for StreamConsumer registrar provider objects.
static interface	KafkaTools.TableType	Type for the result Table returned by kafka consumers.

Field Summary

Fields

Modifier and Type	Field	Description
static final IntPredicate	ALL_PARTITIONS
static final IntToLongFunction	ALL_PARTITIONS_DONT_SEEK
static final IntToLongFunction	ALL_PARTITIONS_SEEK_TO_BEGINNING
static final IntToLongFunction	ALL_PARTITIONS_SEEK_TO_END
static final String	AVRO_DESERIALIZER
static final String	AVRO_LATEST_VERSION
static final String	AVRO_SERIALIZER
static final String	BYTE_ARRAY_DESERIALIZER
static final String	BYTE_ARRAY_SERIALIZER
static final String	BYTE_BUFFER_DESERIALIZER
static final String	BYTE_BUFFER_SERIALIZER
static final String	DESERIALIZER_FOR_IGNORE
static final Function<String,String>	DIRECT_MAPPING
static final long	DONT_SEEK
static final String	DOUBLE_DESERIALIZER
static final String	DOUBLE_SERIALIZER
static final String	FLOAT_DESERIALIZER
static final String	FLOAT_SERIALIZER
static final KafkaTools.Consume.KeyOrValueSpec	FROM_PROPERTIES	The names for the key or value columns can be provided in the properties as "deephaven.key.column.name" or "deephaven.value.column.name", and otherwise default to "KafkaKey" or "KafkaValue".
static final String	INT_DESERIALIZER
static final String	INT_SERIALIZER
static final String	KAFKA_PARTITION_COLUMN_NAME_DEFAULT
static final String	KAFKA_PARTITION_COLUMN_NAME_PROPERTY
static final String	KEY_BYTES_COLUMN_NAME_DEFAULT
static final String	KEY_BYTES_COLUMN_NAME_PROPERTY
static final String	KEY_COLUMN_NAME_DEFAULT
static final String	KEY_COLUMN_NAME_PROPERTY
static final String	KEY_COLUMN_TYPE_PROPERTY
static final String	LONG_DESERIALIZER
static final String	LONG_SERIALIZER
static final String	NESTED_FIELD_COLUMN_NAME_SEPARATOR
static final String	NESTED_FIELD_NAME_SEPARATOR
static final String	OFFSET_COLUMN_NAME_DEFAULT
static final String	OFFSET_COLUMN_NAME_PROPERTY
static final String	RECEIVE_TIME_COLUMN_NAME_DEFAULT
static final String	RECEIVE_TIME_COLUMN_NAME_PROPERTY
static final String	SCHEMA_SERVER_PROPERTY
static final long	SEEK_TO_BEGINNING
static final long	SEEK_TO_END
static final String	SERIALIZER_FOR_IGNORE
static final String	SHORT_DESERIALIZER
static final String	SHORT_SERIALIZER
static final String	STRING_DESERIALIZER
static final String	STRING_SERIALIZER
static final String	TIMESTAMP_COLUMN_NAME_DEFAULT
static final String	TIMESTAMP_COLUMN_NAME_PROPERTY
static final String	VALUE_BYTES_COLUMN_NAME_DEFAULT
static final String	VALUE_BYTES_COLUMN_NAME_PROPERTY
static final String	VALUE_COLUMN_NAME_DEFAULT
static final String	VALUE_COLUMN_NAME_PROPERTY
static final String	VALUE_COLUMN_TYPE_PROPERTY

Constructor Summary

Constructors

Constructor	Description
KafkaTools()

Method Summary

Modifier and Type	Method	Description
static void	avroSchemaToColumnDefinitions(List<ColumnDefinition<?>> columnsOut, Map<String,String> fieldPathToColumnNameOut, org.apache.avro.Schema schema, Function<String,String> requestedFieldPathToColumnName)
static void	avroSchemaToColumnDefinitions(List<ColumnDefinition<?>> columnsOut, Map<String,String> fieldPathToColumnNameOut, org.apache.avro.Schema schema, Function<String,String> requestedFieldPathToColumnName, boolean useUTF8Strings)
static void	avroSchemaToColumnDefinitions(List<ColumnDefinition<?>> columnsOut, org.apache.avro.Schema schema)	Convert an Avro schema to a list of column definitions, mapping every avro field to a column of the same name.
static void	avroSchemaToColumnDefinitions(List<ColumnDefinition<?>> columnsOut, org.apache.avro.Schema schema, Function<String,String> requestedFieldPathToColumnName)	Convert an Avro schema to a list of column definitions.
static org.apache.avro.Schema	columnDefinitionsToAvroSchema(Table t, String schemaName, String namespace, Properties colProps, Predicate<String> includeOnly, Predicate<String> exclude, org.apache.commons.lang3.mutable.MutableObject<Properties> colPropsOut)
static void	consume(@NotNull Properties kafkaProperties, @NotNull String topic, @NotNull IntPredicate partitionFilter, @NotNull KafkaTools.InitialOffsetLookup partitionToInitialOffset, KafkaTools.Consume.KeyOrValueSpec keySpec, KafkaTools.Consume.KeyOrValueSpec valueSpec, @NotNull KafkaTools.StreamConsumerRegistrarProvider streamConsumerRegistrarProvider, @Nullable KafkaTools.ConsumerLoopCallback consumerLoopCallback)	Consume from Kafka to stream consumers supplied by streamConsumerRegistrar.
static PartitionedTable	consumeToPartitionedTable(@NotNull Properties kafkaProperties, @NotNull String topic, @NotNull IntPredicate partitionFilter, @NotNull IntToLongFunction partitionToInitialOffset, KafkaTools.Consume.KeyOrValueSpec keySpec, KafkaTools.Consume.KeyOrValueSpec valueSpec, @NotNull KafkaTools.TableType tableType)	Consume from Kafka to a Deephaven PartitionedTable containing one constituent Table per partition.
static Table	consumeToTable(@NotNull Properties kafkaProperties, @NotNull String topic, @NotNull IntPredicate partitionFilter, @NotNull IntToLongFunction partitionToInitialOffset, KafkaTools.Consume.KeyOrValueSpec keySpec, KafkaTools.Consume.KeyOrValueSpec valueSpec, @NotNull KafkaTools.TableType tableType)	Consume from Kafka to a Deephaven Table.
static KafkaTools.TableType	friendlyNameToTableType(@NotNull String typeName)	Map "Python-friendly" table type name to a KafkaTools.TableType.
static org.apache.avro.Schema	getAvroSchema(String avroSchemaAsJsonString)	Create an Avro schema object for a String containing a JSON encoded Avro schema definition.
static String[]	listTopics(@NotNull Properties kafkaProperties)
static IntPredicate	partitionFilterFromArray(int[] partitions)
static IntToLongFunction	partitionToOffsetFromParallelArrays(int[] partitions, long[] offsets)
static Predicate<String>	predicateFromSet(Set<String> set)
static Runnable	produceFromTable(@NotNull Table table, @NotNull Properties kafkaProperties, @NotNull String topic, KafkaTools.Produce.KeyOrValueSpec keySpec, KafkaTools.Produce.KeyOrValueSpec valueSpec, boolean lastByKeyColumns)	Produce a Kafka stream from a Deephaven table.
static Runnable	produceFromTable(KafkaPublishOptions options)	Produce a Kafka stream from a Deephaven table.
static Set<String>	topics(@NotNull Properties kafkaProperties)

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Details

KAFKA_PARTITION_COLUMN_NAME_PROPERTY

public static final String KAFKA_PARTITION_COLUMN_NAME_PROPERTY

See Also:

• Constant Field Values

KAFKA_PARTITION_COLUMN_NAME_DEFAULT

public static final String KAFKA_PARTITION_COLUMN_NAME_DEFAULT

See Also:

• Constant Field Values

OFFSET_COLUMN_NAME_PROPERTY

public static final String OFFSET_COLUMN_NAME_PROPERTY

See Also:

• Constant Field Values

OFFSET_COLUMN_NAME_DEFAULT

public static final String OFFSET_COLUMN_NAME_DEFAULT

See Also:

• Constant Field Values

TIMESTAMP_COLUMN_NAME_PROPERTY

public static final String TIMESTAMP_COLUMN_NAME_PROPERTY

See Also:

• Constant Field Values

TIMESTAMP_COLUMN_NAME_DEFAULT

public static final String TIMESTAMP_COLUMN_NAME_DEFAULT

See Also:

• Constant Field Values

RECEIVE_TIME_COLUMN_NAME_PROPERTY

public static final String RECEIVE_TIME_COLUMN_NAME_PROPERTY

See Also:

• Constant Field Values

RECEIVE_TIME_COLUMN_NAME_DEFAULT

public static final String RECEIVE_TIME_COLUMN_NAME_DEFAULT

KEY_BYTES_COLUMN_NAME_PROPERTY

public static final String KEY_BYTES_COLUMN_NAME_PROPERTY

See Also:

• Constant Field Values

KEY_BYTES_COLUMN_NAME_DEFAULT

public static final String KEY_BYTES_COLUMN_NAME_DEFAULT

VALUE_BYTES_COLUMN_NAME_PROPERTY

public static final String VALUE_BYTES_COLUMN_NAME_PROPERTY

See Also:

• Constant Field Values

VALUE_BYTES_COLUMN_NAME_DEFAULT

public static final String VALUE_BYTES_COLUMN_NAME_DEFAULT

KEY_COLUMN_NAME_PROPERTY

public static final String KEY_COLUMN_NAME_PROPERTY

See Also:

• Constant Field Values

KEY_COLUMN_NAME_DEFAULT

public static final String KEY_COLUMN_NAME_DEFAULT

See Also:

• Constant Field Values

VALUE_COLUMN_NAME_PROPERTY

public static final String VALUE_COLUMN_NAME_PROPERTY

See Also:

• Constant Field Values

VALUE_COLUMN_NAME_DEFAULT

public static final String VALUE_COLUMN_NAME_DEFAULT

See Also:

• Constant Field Values

KEY_COLUMN_TYPE_PROPERTY

public static final String KEY_COLUMN_TYPE_PROPERTY

See Also:

• Constant Field Values

VALUE_COLUMN_TYPE_PROPERTY

public static final String VALUE_COLUMN_TYPE_PROPERTY

See Also:

• Constant Field Values

SCHEMA_SERVER_PROPERTY

public static final String SCHEMA_SERVER_PROPERTY

See Also:

• Constant Field Values

SHORT_DESERIALIZER

public static final String SHORT_DESERIALIZER

INT_DESERIALIZER

public static final String INT_DESERIALIZER

LONG_DESERIALIZER

public static final String LONG_DESERIALIZER

FLOAT_DESERIALIZER

public static final String FLOAT_DESERIALIZER

DOUBLE_DESERIALIZER

public static final String DOUBLE_DESERIALIZER

BYTE_ARRAY_DESERIALIZER

public static final String BYTE_ARRAY_DESERIALIZER

STRING_DESERIALIZER

public static final String STRING_DESERIALIZER

BYTE_BUFFER_DESERIALIZER

public static final String BYTE_BUFFER_DESERIALIZER

AVRO_DESERIALIZER

public static final String AVRO_DESERIALIZER

DESERIALIZER_FOR_IGNORE

public static final String DESERIALIZER_FOR_IGNORE

SHORT_SERIALIZER

public static final String SHORT_SERIALIZER

INT_SERIALIZER

public static final String INT_SERIALIZER

LONG_SERIALIZER

public static final String LONG_SERIALIZER

FLOAT_SERIALIZER

public static final String FLOAT_SERIALIZER

DOUBLE_SERIALIZER

public static final String DOUBLE_SERIALIZER

BYTE_ARRAY_SERIALIZER

public static final String BYTE_ARRAY_SERIALIZER

STRING_SERIALIZER

public static final String STRING_SERIALIZER

BYTE_BUFFER_SERIALIZER

public static final String BYTE_BUFFER_SERIALIZER

AVRO_SERIALIZER

public static final String AVRO_SERIALIZER

SERIALIZER_FOR_IGNORE

public static final String SERIALIZER_FOR_IGNORE

NESTED_FIELD_NAME_SEPARATOR

public static final String NESTED_FIELD_NAME_SEPARATOR

See Also:

• Constant Field Values

NESTED_FIELD_COLUMN_NAME_SEPARATOR

public static final String NESTED_FIELD_COLUMN_NAME_SEPARATOR

See Also:

• Constant Field Values

AVRO_LATEST_VERSION

public static final String AVRO_LATEST_VERSION

See Also:

• Constant Field Values

SEEK_TO_BEGINNING

public static final long SEEK_TO_BEGINNING

See Also:

• Constant Field Values

DONT_SEEK

public static final long DONT_SEEK

See Also:

• Constant Field Values

SEEK_TO_END

public static final long SEEK_TO_END

See Also:

• Constant Field Values

ALL_PARTITIONS

public static final IntPredicate ALL_PARTITIONS

ALL_PARTITIONS_SEEK_TO_BEGINNING

public static final IntToLongFunction ALL_PARTITIONS_SEEK_TO_BEGINNING

ALL_PARTITIONS_DONT_SEEK

public static final IntToLongFunction ALL_PARTITIONS_DONT_SEEK

ALL_PARTITIONS_SEEK_TO_END

public static final IntToLongFunction ALL_PARTITIONS_SEEK_TO_END

DIRECT_MAPPING

public static final Function<String,String> DIRECT_MAPPING

FROM_PROPERTIES

public static final KafkaTools.Consume.KeyOrValueSpec FROM_PROPERTIES

The names for the key or value columns can be provided in the properties as "deephaven.key.column.name" or "deephaven.value.column.name", and otherwise default to "KafkaKey" or "KafkaValue". The types for key or value are either specified in the properties as "deephaven.key.column.type" or "deephaven.value.column.type" or deduced from the serializer classes for "key.deserializer" or "value.deserializer" in the provided Properties object.

Constructor Details

KafkaTools

public KafkaTools()

Method Details

getAvroSchema

public static org.apache.avro.Schema getAvroSchema(String avroSchemaAsJsonString)

Create an Avro schema object for a String containing a JSON encoded Avro schema definition.

Parameters:

avroSchemaAsJsonString - The JSON Avro schema definition

Returns:

an Avro schema object

columnDefinitionsToAvroSchema

public static org.apache.avro.Schema columnDefinitionsToAvroSchema(Table t,
 String schemaName,
 String namespace,
 Properties colProps,
 Predicate<String> includeOnly,
 Predicate<String> exclude,
 org.apache.commons.lang3.mutable.MutableObject<Properties> colPropsOut)

avroSchemaToColumnDefinitions

public static void avroSchemaToColumnDefinitions(List<ColumnDefinition<?>> columnsOut,
 Map<String,String> fieldPathToColumnNameOut,
 org.apache.avro.Schema schema,
 Function<String,String> requestedFieldPathToColumnName)

avroSchemaToColumnDefinitions

public static void avroSchemaToColumnDefinitions(List<ColumnDefinition<?>> columnsOut,
 Map<String,String> fieldPathToColumnNameOut,
 org.apache.avro.Schema schema,
 Function<String,String> requestedFieldPathToColumnName,
 boolean useUTF8Strings)

avroSchemaToColumnDefinitions

public static void avroSchemaToColumnDefinitions(List<ColumnDefinition<?>> columnsOut,
 org.apache.avro.Schema schema,
 Function<String,String> requestedFieldPathToColumnName)

Convert an Avro schema to a list of column definitions.

Parameters:

columnsOut - Column definitions for output; should be empty on entry.

schema - Avro schema

requestedFieldPathToColumnName - An optional mapping to specify selection and naming of columns from Avro fields, or null for map all fields using field path for column name.

avroSchemaToColumnDefinitions

public static void avroSchemaToColumnDefinitions(List<ColumnDefinition<?>> columnsOut,
 org.apache.avro.Schema schema)

Convert an Avro schema to a list of column definitions, mapping every avro field to a column of the same name.

Parameters:

columnsOut - Column definitions for output; should be empty on entry.

schema - Avro schema

friendlyNameToTableType

@ScriptApi
public static KafkaTools.TableType friendlyNameToTableType(@NotNull
 @NotNull String typeName)

Map "Python-friendly" table type name to a KafkaTools.TableType. Supported values are:

1. "blink"
2. "stream" (deprecated; use "blink")
3. "append"
4. "ring:<capacity>" where capacity is a integer number specifying the maximum number of trailing rows to include in the result

Parameters:

typeName - The friendly name

Returns:

The mapped KafkaTools.TableType

consumeToTable

public static Table consumeToTable(@NotNull
 @NotNull Properties kafkaProperties,
 @NotNull
 @NotNull String topic,
 @NotNull
 @NotNull IntPredicate partitionFilter,
 @NotNull
 @NotNull IntToLongFunction partitionToInitialOffset,
 @NotNull
 KafkaTools.Consume.KeyOrValueSpec keySpec,
 @NotNull
 KafkaTools.Consume.KeyOrValueSpec valueSpec,
 @NotNull
 @NotNull KafkaTools.TableType tableType)

Consume from Kafka to a Deephaven Table.

Parameters:

kafkaProperties - Properties to configure the result and also to be passed to create the KafkaConsumer

topic - Kafka topic name

partitionFilter - A predicate returning true for the partitions to consume. The convenience constant ALL_PARTITIONS is defined to facilitate requesting all partitions.

partitionToInitialOffset - A function specifying the desired initial offset for each partition consumed

keySpec - Conversion specification for Kafka record keys

valueSpec - Conversion specification for Kafka record values

tableType - KafkaTools.TableType specifying the type of the expected result

Returns:

The result Table containing Kafka stream data formatted according to tableType

consumeToPartitionedTable

public static PartitionedTable consumeToPartitionedTable(@NotNull
 @NotNull Properties kafkaProperties,
 @NotNull
 @NotNull String topic,
 @NotNull
 @NotNull IntPredicate partitionFilter,
 @NotNull
 @NotNull IntToLongFunction partitionToInitialOffset,
 @NotNull
 KafkaTools.Consume.KeyOrValueSpec keySpec,
 @NotNull
 KafkaTools.Consume.KeyOrValueSpec valueSpec,
 @NotNull
 @NotNull KafkaTools.TableType tableType)

Consume from Kafka to a Deephaven PartitionedTable containing one constituent Table per partition.

Parameters:

kafkaProperties - Properties to configure the result and also to be passed to create the KafkaConsumer

topic - Kafka topic name

partitionFilter - A predicate returning true for the partitions to consume. The convenience constant ALL_PARTITIONS is defined to facilitate requesting all partitions.

partitionToInitialOffset - A function specifying the desired initial offset for each partition consumed

keySpec - Conversion specification for Kafka record keys

valueSpec - Conversion specification for Kafka record values

tableType - KafkaTools.TableType specifying the type of the expected result's constituent tables

Returns:

The result PartitionedTable containing Kafka stream data formatted according to tableType

consume

public static void consume(@NotNull
 @NotNull Properties kafkaProperties,
 @NotNull
 @NotNull String topic,
 @NotNull
 @NotNull IntPredicate partitionFilter,
 @NotNull
 @NotNull KafkaTools.InitialOffsetLookup partitionToInitialOffset,
 @NotNull
 KafkaTools.Consume.KeyOrValueSpec keySpec,
 @NotNull
 KafkaTools.Consume.KeyOrValueSpec valueSpec,
 @NotNull
 @NotNull KafkaTools.StreamConsumerRegistrarProvider streamConsumerRegistrarProvider,
 @Nullable
 @Nullable KafkaTools.ConsumerLoopCallback consumerLoopCallback)

Consume from Kafka to stream consumers supplied by streamConsumerRegistrar.

Parameters:

kafkaProperties - Properties to configure this table and also to be passed to create the KafkaConsumer

topic - Kafka topic name

partitionFilter - A predicate returning true for the partitions to consume. The convenience constant ALL_PARTITIONS is defined to facilitate requesting all partitions.

partitionToInitialOffset - A function specifying the desired initial offset for each partition consumed

keySpec - Conversion specification for Kafka record keys

valueSpec - Conversion specification for Kafka record values

streamConsumerRegistrarProvider - A provider for a function to register StreamConsumer instances. The registered stream consumers must accept chunk types that correspond to StreamChunkUtils.chunkTypeForColumnIndex(TableDefinition, int) for the supplied TableDefinition. See single and per-partition.

consumerLoopCallback - callback to inject logic into the ingester's consumer loop

produceFromTable

public static Runnable produceFromTable(@NotNull
 @NotNull Table table,
 @NotNull
 @NotNull Properties kafkaProperties,
 @NotNull
 @NotNull String topic,
 @NotNull
 KafkaTools.Produce.KeyOrValueSpec keySpec,
 @NotNull
 KafkaTools.Produce.KeyOrValueSpec valueSpec,
 boolean lastByKeyColumns)

Produce a Kafka stream from a Deephaven table.

Note that table must only change in ways that are meaningful when turned into a stream of events over Kafka.

Two primary use cases are considered:

1. A stream of changes (puts and removes) to a key-value data set. In order to handle this efficiently and allow for correct reconstruction of the state at a consumer, it is assumed that the input data is the result of a Deephaven aggregation, e.g. TableOperations.aggAllBy(io.deephaven.api.agg.spec.AggSpec), TableOperations.aggBy(io.deephaven.api.agg.Aggregation), or TableOperations.lastBy(). This means that key columns (as specified by keySpec) must not be modified, and no rows should be shifted if there are any key columns. Note that specifying lastByKeyColumns=true can make it easy to satisfy this constraint if the input data is not already aggregated.
2. A stream of independent log records. In this case, the input table should either be a blink table or should only ever add rows (regardless of whether the attribute is specified).

If other use cases are identified, a publication mode or extensible listener framework may be introduced at a later date.

Parameters:

table - The table used as a source of data to be sent to Kafka.

kafkaProperties - Properties to be passed to create the associated KafkaProducer.

topic - Kafka topic name

keySpec - Conversion specification for Kafka record keys from table column data.

valueSpec - Conversion specification for Kafka record values from table column data.

lastByKeyColumns - Whether to publish only the last record for each unique key. Ignored when keySpec is IGNORE. Otherwise, if lastByKeycolumns == true this method will internally perform a lastBy aggregation on table grouped by the input columns of keySpec and publish to Kafka from the result.

Returns:

a callback to stop producing and shut down the associated table listener; note a caller should keep a reference to this return value to ensure liveliness.

See Also:

• produceFromTable(KafkaPublishOptions)

produceFromTable

public static Runnable produceFromTable(KafkaPublishOptions options)

Produce a Kafka stream from a Deephaven table.

Note that table must only change in ways that are meaningful when turned into a stream of events over Kafka.

Two primary use cases are considered:

1. A stream of changes (puts and removes) to a key-value data set. In order to handle this efficiently and allow for correct reconstruction of the state at a consumer, it is assumed that the input data is the result of a Deephaven aggregation, e.g. TableOperations.aggAllBy(io.deephaven.api.agg.spec.AggSpec), TableOperations.aggBy(io.deephaven.api.agg.Aggregation), or TableOperations.lastBy(). This means that key columns (as specified by keySpec) must not be modified, and no rows should be shifted if there are any key columns. Note that specifying lastByKeyColumns=true can make it easy to satisfy this constraint if the input data is not already aggregated.
2. A stream of independent log records. In this case, the input table should either be a blink table or should only ever add rows (regardless of whether the attribute is specified).

If other use cases are identified, a publication mode or extensible listener framework may be introduced at a later date.

Parameters:

options - the options

Returns:

a callback to stop producing and shut down the associated table listener; note a caller should keep a reference to this return value to ensure liveliness.

partitionFilterFromArray

public static IntPredicate partitionFilterFromArray(int[] partitions)

partitionToOffsetFromParallelArrays

public static IntToLongFunction partitionToOffsetFromParallelArrays(int[] partitions,
 long[] offsets)

predicateFromSet

public static Predicate<String> predicateFromSet(Set<String> set)

topics

public static Set<String> topics(@NotNull
 @NotNull Properties kafkaProperties)

listTopics

public static String[] listTopics(@NotNull
 @NotNull Properties kafkaProperties)