druid-runtime-historical

druid.extensions.coordinates=["org.apache.hadoop:hadoop-client:2.4.0", "io.druid.extensions:druid-kafka-eight","io.druid.extensions:mysql-metadata-storage", "io.druid.extensions:druid-hdfs-storage"]

# Zookeeper
druid.zk.service.host=kafka.advertine.com:2181/kafka081

# Metadata Storage (mysql)
druid.metadata.storage.type=mysql
druid.metadata.storage.connector.connectURI=jdbc\:mysql\://web.advertine.com\:3306/druid
druid.metadata.storage.connector.user=root
druid.metadata.storage.connector.password=
druid.metadata.storage.connector.createTables=true

# Deep storage (local filesystem for examples - don't use this in production)
#druid.storage.type=local
#druid.storage.storage.storageDirectory=/tmp/druid/localStorage

druid.cache.type=local
druid.cache.sizeInBytes=300000000

# Indexing service discovery
druid.selectors.indexing.serviceName=overlord

# Monitoring (disabled for examples)
# druid.monitoring.monitors=["com.metamx.metrics.JvmMonitor"]

# Metrics logging (disabled for examples)
druid.emitter=noop

# We enable using the local query cache here
druid.broker.cache.useCache=true
druid.broker.cache.populateCache=true

# Bump these up only for faster nested groupBy
druid.processing.buffer.sizeBytes=1000000000
druid.processing.numThreads=4

#druid.host=localhost
druid.port=9084
druid.service=historical

# We can only 1 scan segment in parallel with these configs.
# Our intermediate buffer is also very small so longer topNs will be slow.
druid.segmentCache.locations=[{"path": "/home/druid/cache/historical1/indexCache", "maxSize": 10000000000}]
druid.server.maxSize=100000000000

druid.storage.type=hdfs
druid.storage.storageDirectory=/user/druid