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Kafka: Integrating Engine tables with Kafka
/**
* Copyright (c) 2016-2022 Deephaven Data Labs and Patent Pending
*/
package io.deephaven.kafka;
import io.confluent.kafka.schemaregistry.SchemaProvider;
import io.confluent.kafka.schemaregistry.avro.AvroSchema;
import io.confluent.kafka.schemaregistry.avro.AvroSchemaProvider;
import io.confluent.kafka.schemaregistry.client.SchemaMetadata;
import io.confluent.kafka.schemaregistry.client.SchemaRegistryClient;
import io.confluent.kafka.schemaregistry.client.rest.exceptions.RestClientException;
import io.confluent.kafka.serializers.KafkaAvroDeserializer;
import io.confluent.kafka.serializers.KafkaAvroSerializer;
import io.deephaven.UncheckedDeephavenException;
import io.deephaven.engine.table.ColumnDefinition;
import io.deephaven.engine.table.Table;
import io.deephaven.engine.table.TableDefinition;
import io.deephaven.engine.util.BigDecimalUtils;
import io.deephaven.kafka.KafkaTools.Consume;
import io.deephaven.kafka.KafkaTools.KeyOrValue;
import io.deephaven.kafka.KafkaTools.KeyOrValueIngestData;
import io.deephaven.kafka.KafkaTools.Produce;
import io.deephaven.kafka.ingest.GenericRecordChunkAdapter;
import io.deephaven.kafka.ingest.KeyOrValueProcessor;
import io.deephaven.kafka.publish.GenericRecordKeyOrValueSerializer;
import io.deephaven.kafka.publish.KeyOrValueSerializer;
import io.deephaven.qst.type.Type;
import io.deephaven.stream.StreamChunkUtils;
import io.deephaven.vector.ByteVector;
import org.apache.avro.LogicalType;
import org.apache.avro.LogicalTypes;
import org.apache.avro.Schema;
import org.apache.avro.Schema.Field;
import org.apache.avro.SchemaBuilder;
import org.apache.avro.generic.GenericContainer;
import org.apache.avro.generic.GenericRecord;
import org.apache.avro.util.Utf8;
import org.apache.commons.lang3.mutable.MutableInt;
import org.apache.commons.lang3.mutable.MutableObject;
import org.apache.kafka.common.header.Headers;
import org.apache.kafka.common.serialization.Deserializer;
import org.apache.kafka.common.serialization.Serializer;
import org.jetbrains.annotations.NotNull;
import java.io.IOException;
import java.math.BigDecimal;
import java.time.Instant;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Objects;
import java.util.Optional;
import java.util.Properties;
import java.util.function.Function;
import java.util.function.Predicate;
import java.util.regex.Pattern;
import static io.deephaven.kafka.KafkaTools.AVRO_LATEST_VERSION;
import static io.deephaven.kafka.KafkaTools.NESTED_FIELD_NAME_SEPARATOR;
class AvroImpl {
private static final Type utf8Type = Type.find(Utf8.class);
static final class AvroConsume extends Consume.KeyOrValueSpec {
private static final Pattern NESTED_FIELD_NAME_SEPARATOR_PATTERN =
Pattern.compile(Pattern.quote(NESTED_FIELD_NAME_SEPARATOR));
private Schema schema;
private final String schemaName;
private final String schemaVersion;
/** fields mapped to null are skipped. */
private final Function fieldPathToColumnName;
private final boolean useUTF8Strings;
AvroConsume(final Schema schema, final Function fieldPathToColumnName) {
this.schema = Objects.requireNonNull(schema);
this.schemaName = null;
this.schemaVersion = null;
this.fieldPathToColumnName = fieldPathToColumnName;
this.useUTF8Strings = false;
}
AvroConsume(final String schemaName,
final String schemaVersion,
final Function fieldPathToColumnName) {
this(schemaName, schemaVersion, fieldPathToColumnName, false);
}
AvroConsume(final String schemaName,
final String schemaVersion,
final Function fieldPathToColumnName,
final boolean useUTF8Strings) {
this.schema = null;
this.schemaName = schemaName;
this.schemaVersion = schemaVersion;
this.fieldPathToColumnName = fieldPathToColumnName;
this.useUTF8Strings = useUTF8Strings;
}
@Override
public Optional getSchemaProvider() {
return Optional.of(new AvroSchemaProvider());
}
@Override
protected Deserializer getDeserializer(KeyOrValue keyOrValue, SchemaRegistryClient schemaRegistryClient,
Map configs) {
ensureSchema(schemaRegistryClient);
return new KafkaAvroDeserializerWithReaderSchema(schemaRegistryClient);
}
@Override
protected KeyOrValueIngestData getIngestData(KeyOrValue keyOrValue,
SchemaRegistryClient schemaRegistryClient, Map configs, MutableInt nextColumnIndexMut,
List> columnDefinitionsOut) {
ensureSchema(schemaRegistryClient);
KeyOrValueIngestData data = new KeyOrValueIngestData();
data.fieldPathToColumnName = new HashMap<>();
avroSchemaToColumnDefinitions(columnDefinitionsOut, data.fieldPathToColumnName, schema,
fieldPathToColumnName, useUTF8Strings);
data.extra = schema;
return data;
}
@Override
protected KeyOrValueProcessor getProcessor(TableDefinition tableDef, KeyOrValueIngestData data) {
return GenericRecordChunkAdapter.make(
tableDef,
ci -> StreamChunkUtils.chunkTypeForColumnIndex(tableDef, ci),
data.fieldPathToColumnName,
NESTED_FIELD_NAME_SEPARATOR_PATTERN,
(Schema) data.extra,
true);
}
private void ensureSchema(SchemaRegistryClient schemaRegistryClient) {
// This adds a little bit of stateful-ness to AvroConsume. Typically, this is not something we want /
// encourage for implementations, but due to the getDeserializer / getProcessor dependency on the exact
// same schema, we need to ensure we don't race if the user has set AVRO_LATEST_VERSION. Alternatively, we
// could break the KeyOrValueSpec API and pass Deserializer as parameter to getIngestData.
if (schema != null) {
return;
}
schema = Objects.requireNonNull(getAvroSchema(schemaRegistryClient, schemaName, schemaVersion));
}
/**
* Our getProcessor relies on a specific {@link Schema}; we need to ensure that Kafka layer adapts the on-wire
* writer's schema to our reader's schema.
*/
class KafkaAvroDeserializerWithReaderSchema extends KafkaAvroDeserializer {
public KafkaAvroDeserializerWithReaderSchema(SchemaRegistryClient client) {
super(client);
}
@Override
public java.lang.Object deserialize(String topic, byte[] bytes) {
return super.deserialize(topic, bytes, schema);
}
@Override
public java.lang.Object deserialize(String topic, Headers headers, byte[] bytes) {
return super.deserialize(topic, headers, bytes, schema);
}
}
}
static final class AvroProduce extends Produce.KeyOrValueSpec {
private Schema schema;
private final String schemaName;
private final String schemaVersion;
final Map fieldToColumnMapping;
private final String timestampFieldName;
private final Predicate includeOnlyColumns;
private final Predicate excludeColumns;
private final boolean publishSchema;
private final String schemaNamespace;
private final MutableObject columnProperties;
AvroProduce(final Schema schema,
final String schemaName,
final String schemaVersion,
final Map fieldToColumnMapping,
final String timestampFieldName,
final Predicate includeOnlyColumns,
final Predicate excludeColumns,
final boolean publishSchema,
final String schemaNamespace,
final Properties columnProperties) {
this.schema = schema;
this.schemaName = schemaName;
this.schemaVersion = schemaVersion;
this.fieldToColumnMapping = fieldToColumnMapping;
this.timestampFieldName = timestampFieldName;
this.includeOnlyColumns = includeOnlyColumns;
this.excludeColumns = excludeColumns;
this.publishSchema = publishSchema;
this.schemaNamespace = schemaNamespace;
this.columnProperties = new MutableObject<>(columnProperties);
if (publishSchema) {
if (schemaVersion != null && !AVRO_LATEST_VERSION.equals(schemaVersion)) {
throw new IllegalArgumentException(
String.format("schemaVersion must be null or \"%s\" when publishSchema=true",
AVRO_LATEST_VERSION));
}
}
}
@Override
public Optional getSchemaProvider() {
return Optional.of(new AvroSchemaProvider());
}
@Override
Serializer getSerializer(SchemaRegistryClient schemaRegistryClient, TableDefinition definition) {
return new KafkaAvroSerializer(Objects.requireNonNull(schemaRegistryClient));
}
@Override
String[] getColumnNames(@NotNull final Table t, SchemaRegistryClient schemaRegistryClient) {
ensureSchema(t, schemaRegistryClient);
final List fields = schema.getFields();
// ensure we got timestampFieldName right
if (timestampFieldName != null) {
boolean found = false;
for (final Field field : fields) {
final String fieldName = field.name();
if (fieldName.equals(timestampFieldName)) {
found = true;
break;
}
}
if (!found) {
throw new IllegalArgumentException(
"timestampFieldName=" + timestampFieldName +
" is not a field name in the provided schema.");
}
}
final int timestampFieldCount = ((timestampFieldName != null) ? 1 : 0);
final List columnNames = new ArrayList<>();
for (final Field field : fields) {
final String fieldName = field.name();
if (fieldName.equals(timestampFieldName)) {
continue;
}
final String candidateColumnName;
if (fieldToColumnMapping == null) {
candidateColumnName = fieldName;
} else {
candidateColumnName = fieldToColumnMapping.getOrDefault(fieldName, fieldName);
}
if (excludeColumns != null && excludeColumns.test(candidateColumnName)) {
continue;
}
if (includeOnlyColumns != null && !includeOnlyColumns.test(candidateColumnName)) {
continue;
}
columnNames.add(candidateColumnName);
}
return columnNames.toArray(new String[columnNames.size()]);
}
@Override
KeyOrValueSerializer getKeyOrValueSerializer(@NotNull Table t, @NotNull String[] columnNames) {
return new GenericRecordKeyOrValueSerializer(
t, schema, columnNames, timestampFieldName, columnProperties.getValue());
}
void ensureSchema(final Table t, SchemaRegistryClient schemaRegistryClient) {
if (schema != null) {
return;
}
if (publishSchema) {
schema = columnDefinitionsToAvroSchema(t,
schemaName, schemaNamespace, columnProperties.getValue(), includeOnlyColumns,
excludeColumns, columnProperties);
try {
schemaRegistryClient.register(schemaName, new AvroSchema(schema));
} catch (RestClientException | IOException e) {
throw new UncheckedDeephavenException(e);
}
} else {
schema = getAvroSchema(schemaRegistryClient, schemaName, schemaVersion);
}
}
}
static Schema getAvroSchema(SchemaRegistryClient schemaClient, final String schemaName,
final String schemaVersion) {
try {
final SchemaMetadata schemaMetadata;
if (AVRO_LATEST_VERSION.equals(schemaVersion)) {
schemaMetadata = schemaClient.getLatestSchemaMetadata(schemaName);
} else {
schemaMetadata = schemaClient.getSchemaMetadata(schemaName, Integer.parseInt(schemaVersion));
}
return (Schema) schemaClient.getSchemaById(schemaMetadata.getId()).rawSchema();
} catch (RestClientException | IOException e) {
throw new UncheckedDeephavenException(e);
}
}
static Schema columnDefinitionsToAvroSchema(Table t, String schemaName, String namespace, Properties colProps,
Predicate includeOnly, Predicate exclude, MutableObject colPropsOut) {
SchemaBuilder.FieldAssembler fass = SchemaBuilder.record(schemaName).namespace(namespace).fields();
final List> colDefs = t.getDefinition().getColumns();
colPropsOut.setValue(colProps);
for (final ColumnDefinition colDef : colDefs) {
if (includeOnly != null && !includeOnly.test(colDef.getName())) {
continue;
}
if (exclude != null && exclude.test(colDef.getName())) {
continue;
}
fass = addFieldForColDef(t, fass, colDef, colPropsOut);
}
return fass.endRecord();
}
private static SchemaBuilder.FieldAssembler addFieldForColDef(
final Table t,
final SchemaBuilder.FieldAssembler fassIn,
final ColumnDefinition colDef,
final MutableObject colPropsMu) {
final String logicalTypeName = "logicalType";
final String dhTypeAttribute = "dhType";
SchemaBuilder.FieldAssembler fass = fassIn;
final Class type = colDef.getDataType();
final String colName = colDef.getName();
final SchemaBuilder.BaseFieldTypeBuilder base = fass.name(colName).type().nullable();
if (type == byte.class || type == char.class || type == short.class) {
fass = base.intBuilder().prop(dhTypeAttribute, type.getName()).endInt().noDefault();
} else if (type == int.class) {
fass = base.intType().noDefault();
} else if (type == long.class) {
fass = base.longType().noDefault();
} else if (type == float.class) {
fass = base.floatType().noDefault();
} else if (type == double.class) {
fass = base.doubleType().noDefault();
} else if (type == String.class) {
fass = base.stringType().noDefault();
} else if (type == Instant.class) {
fass = base.longBuilder().prop(logicalTypeName, "timestamp-micros").endLong().noDefault();
} else if (type == BigDecimal.class) {
final BigDecimalUtils.PropertyNames propertyNames =
new BigDecimalUtils.PropertyNames(colName);
BigDecimalUtils.PrecisionAndScale values =
BigDecimalUtils.getPrecisionAndScaleFromColumnProperties(propertyNames, colPropsMu.getValue(),
true);
if (t.isRefreshing()) {
validatePrecisionAndScaleForRefreshingTable(propertyNames, values);
} else { // non refreshing table
ensurePrecisionAndScaleForStaticTable(colPropsMu, t, propertyNames, values);
}
fass = base.bytesBuilder()
.prop(logicalTypeName, "decimal")
.prop("precision", values.precision)
.prop("scale", values.scale)
.endBytes()
.noDefault();
} else {
fass = base.bytesBuilder().prop(dhTypeAttribute, type.getName()).endBytes().noDefault();
}
return fass;
}
private static void validatePrecisionAndScaleForRefreshingTable(
final BigDecimalUtils.PropertyNames names,
final BigDecimalUtils.PrecisionAndScale values) {
final String exBaseMsg = "Column " + names.columnName + " of type " + BigDecimal.class.getSimpleName() +
" in a refreshing table implies both properties '" +
names.precisionProperty + "' and '" + names.scaleProperty
+ "' should be defined; ";
if (values.precision == BigDecimalUtils.INVALID_PRECISION_OR_SCALE
&& values.scale == BigDecimalUtils.INVALID_PRECISION_OR_SCALE) {
throw new IllegalArgumentException(exBaseMsg + " missing both");
}
if (values.precision == BigDecimalUtils.INVALID_PRECISION_OR_SCALE) {
throw new IllegalArgumentException(
exBaseMsg + " missing '" + names.precisionProperty + "'");
}
if (values.scale == BigDecimalUtils.INVALID_PRECISION_OR_SCALE) {
throw new IllegalArgumentException(exBaseMsg + " missing '" + names.scaleProperty + "'");
}
}
private static BigDecimalUtils.PrecisionAndScale ensurePrecisionAndScaleForStaticTable(
final MutableObject colPropsMu,
final Table t,
final BigDecimalUtils.PropertyNames names,
final BigDecimalUtils.PrecisionAndScale valuesIn) {
if (valuesIn.precision != BigDecimalUtils.INVALID_PRECISION_OR_SCALE
&& valuesIn.scale != BigDecimalUtils.INVALID_PRECISION_OR_SCALE) {
return valuesIn;
}
final String exBaseMsg = "Column " + names.columnName + " of type " + BigDecimal.class.getSimpleName() +
" in a non refreshing table implies either both properties '" +
names.precisionProperty + "' and '" + names.scaleProperty
+ "' should be defined, or none of them;";
if (valuesIn.precision != BigDecimalUtils.INVALID_PRECISION_OR_SCALE) {
throw new IllegalArgumentException(
exBaseMsg + " only '" + names.precisionProperty + "' is defined, missing '"
+ names.scaleProperty + "'");
}
if (valuesIn.scale != BigDecimalUtils.INVALID_PRECISION_OR_SCALE) {
throw new IllegalArgumentException(
exBaseMsg + " only '" + names.scaleProperty + "' is defined, missing '"
+ names.precisionProperty + "'");
}
// Both precision and scale are null; compute them ourselves.
final BigDecimalUtils.PrecisionAndScale newValues =
BigDecimalUtils.computePrecisionAndScale(t, names.columnName);
final Properties toSet;
final Properties colProps = colPropsMu.getValue();
if (colProps == null) {
toSet = new Properties();
colPropsMu.setValue(toSet);
} else {
toSet = colProps;
}
BigDecimalUtils.setProperties(toSet, names, newValues);
return newValues;
}
static void avroSchemaToColumnDefinitions(List> columnsOut,
Map fieldPathToColumnNameOut, Schema schema,
Function requestedFieldPathToColumnName,
final boolean useUTF8Strings) {
if (schema.isUnion()) {
throw new UnsupportedOperationException("Schemas defined as a union of records are not supported");
}
final Schema.Type type = schema.getType();
if (type != Schema.Type.RECORD) {
throw new IllegalArgumentException("The schema is not a toplevel record definition.");
}
final List fields = schema.getFields();
for (final Field field : fields) {
pushColumnTypesFromAvroField(columnsOut, fieldPathToColumnNameOut, "", field,
requestedFieldPathToColumnName, useUTF8Strings);
}
}
private static void pushColumnTypesFromAvroField(
final List> columnsOut,
final Map fieldPathToColumnNameOut,
final String fieldNamePrefix,
final Field field,
final Function fieldPathToColumnName,
final boolean useUTF8Strings) {
final Schema fieldSchema = field.schema();
final String fieldName = field.name();
final String mappedNameForColumn = fieldPathToColumnName.apply(fieldNamePrefix + fieldName);
if (mappedNameForColumn == null) {
// allow the user to specify fields to skip by providing a mapping to null.
return;
}
final Schema.Type fieldType = fieldSchema.getType();
pushColumnTypesFromAvroField(
columnsOut, fieldPathToColumnNameOut,
fieldNamePrefix, fieldName,
fieldSchema, mappedNameForColumn, fieldType, fieldPathToColumnName, useUTF8Strings);
}
private static void pushColumnTypesFromAvroField(
final List> columnsOut,
final Map fieldPathToColumnNameOut,
final String fieldNamePrefix,
final String fieldName,
final Schema fieldSchema,
final String mappedNameForColumn,
final Schema.Type fieldType,
final Function fieldPathToColumnName,
final boolean useUTF8Strings) {
switch (fieldType) {
case BOOLEAN:
columnsOut.add(ColumnDefinition.ofBoolean(mappedNameForColumn));
break;
// There is no "SHORT" in Avro.
case INT:
columnsOut.add(ColumnDefinition.ofInt(mappedNameForColumn));
break;
case LONG: {
final LogicalType logicalType = getEffectiveLogicalType(fieldName, fieldSchema);
if (LogicalTypes.timestampMicros().equals(logicalType) ||
LogicalTypes.timestampMillis().equals(logicalType)) {
columnsOut.add(ColumnDefinition.ofTime(mappedNameForColumn));
} else {
columnsOut.add(ColumnDefinition.ofLong(mappedNameForColumn));
}
break;
}
case FLOAT:
columnsOut.add(ColumnDefinition.ofFloat(mappedNameForColumn));
break;
case DOUBLE:
columnsOut.add(ColumnDefinition.ofDouble(mappedNameForColumn));
break;
case ENUM:
case STRING:
if (useUTF8Strings) {
columnsOut.add(ColumnDefinition.of(mappedNameForColumn, utf8Type));
} else {
columnsOut.add(ColumnDefinition.ofString(mappedNameForColumn));
}
break;
case UNION: {
final Schema effectiveSchema = KafkaSchemaUtils.getEffectiveSchema(fieldName, fieldSchema);
if (effectiveSchema == fieldSchema) {
// It is an honest to god Union; we don't support them right now other than giving back
// an Object column with a GenericRecord object.
columnsOut.add(ColumnDefinition.fromGenericType(mappedNameForColumn, GenericRecord.class));
break;
}
// It was a union with null, which is simply the other unioned type in DH.
pushColumnTypesFromAvroField(
columnsOut, fieldPathToColumnNameOut,
fieldNamePrefix, fieldName,
effectiveSchema, mappedNameForColumn, effectiveSchema.getType(), fieldPathToColumnName,
useUTF8Strings);
return;
}
case RECORD:
// Linearize any nesting.
for (final Field nestedField : fieldSchema.getFields()) {
pushColumnTypesFromAvroField(
columnsOut, fieldPathToColumnNameOut,
fieldNamePrefix + fieldName + NESTED_FIELD_NAME_SEPARATOR, nestedField,
fieldPathToColumnName, useUTF8Strings);
}
return;
case BYTES:
case FIXED: {
final LogicalType logicalType = getEffectiveLogicalType(fieldName, fieldSchema);
if (logicalType instanceof LogicalTypes.Decimal) {
columnsOut.add(ColumnDefinition.fromGenericType(mappedNameForColumn, BigDecimal.class));
break;
}
columnsOut.add(ColumnDefinition.ofVector(mappedNameForColumn, ByteVector.class));
break;
}
case ARRAY: {
Schema elementTypeSchema = fieldSchema.getElementType();
Schema.Type elementTypeType = elementTypeSchema.getType();
if (elementTypeType.equals(Schema.Type.UNION)) {
elementTypeSchema = KafkaSchemaUtils.getEffectiveSchema(fieldName, elementTypeSchema);
elementTypeType = elementTypeSchema.getType();
}
switch (elementTypeType) {
case INT:
columnsOut.add(ColumnDefinition.fromGenericType(mappedNameForColumn, int[].class));
break;
case LONG:
final LogicalType logicalType = getEffectiveLogicalType(fieldName, elementTypeSchema);
if (LogicalTypes.timestampMicros().equals(logicalType) ||
LogicalTypes.timestampMillis().equals(logicalType)) {
columnsOut.add(ColumnDefinition.fromGenericType(mappedNameForColumn, Instant[].class));
} else {
columnsOut.add(ColumnDefinition.fromGenericType(mappedNameForColumn, long[].class));
}
break;
case FLOAT:
columnsOut.add(ColumnDefinition.fromGenericType(mappedNameForColumn, float[].class));
break;
case DOUBLE:
columnsOut.add(ColumnDefinition.fromGenericType(mappedNameForColumn, double[].class));
break;
case BOOLEAN:
columnsOut.add(ColumnDefinition.fromGenericType(mappedNameForColumn, Boolean[].class));
break;
case ENUM:
case STRING:
columnsOut.add(ColumnDefinition.fromGenericType(mappedNameForColumn, String[].class));
break;
default:
columnsOut.add(ColumnDefinition.fromGenericType(mappedNameForColumn, Object[].class));
break;
}
break;
}
case MAP:
columnsOut.add(ColumnDefinition.fromGenericType(mappedNameForColumn, Map.class));
break;
case NULL:
default:
columnsOut.add(ColumnDefinition.fromGenericType(mappedNameForColumn, GenericContainer.class));
break;
}
if (fieldPathToColumnNameOut != null) {
fieldPathToColumnNameOut.put(fieldNamePrefix + fieldName, mappedNameForColumn);
}
}
private static LogicalType getEffectiveLogicalType(final String fieldName, final Schema fieldSchema) {
final Schema effectiveSchema = KafkaSchemaUtils.getEffectiveSchema(fieldName, fieldSchema);
return effectiveSchema.getLogicalType();
}
}
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