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Relocating Table Schema Building: Shifting from Brokers to Coordinator for Improved Efficiency (#14985) In the current design, brokers query both data nodes and tasks to fetch the schema of the segments they serve. The table schema is then constructed by combining the schemas of all segments within a datasource. However, this approach leads to a high number of segment metadata queries during broker startup, resulting in slow startup times and various issues outlined in the design proposal. To address these challenges, we propose centralizing the table schema management process within the coordinator. This change is the first step in that direction. In the new arrangement, the coordinator will take on the responsibility of querying both data nodes and tasks to fetch segment schema and subsequently building the table schema. Brokers will now simply query the Coordinator to fetch table schema. Importantly, brokers will still retain the capability to build table schemas if the need arises, ensuring both flexibility and resilience.
2023-11-04 10:03:25 -04:00
# Licensed to the Apache Software Foundation (ASF) under one or more
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# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
version: "2.2"
services:
druid-zookeeper-kafka:
extends:
file: docker-compose.base.yml
service: druid-zookeeper-kafka
druid-metadata-storage:
extends:
file: docker-compose.base.yml
service: druid-metadata-storage
environment:
- DRUID_INTEGRATION_TEST_GROUP=${DRUID_INTEGRATION_TEST_GROUP}
depends_on:
- druid-zookeeper-kafka
druid-coordinator:
extends:
file: docker-compose.base.yml
service: druid-coordinator
environment:
- DRUID_INTEGRATION_TEST_GROUP=${DRUID_INTEGRATION_TEST_GROUP}
Rename config for enabling CentralizedDatasourceSchema feature (#15476) * Rename property to druid.centralizedDatasourceSchema.enabled * Update config name in docker-compose
2023-12-05 06:27:25 -05:00
- druid_centralizedDatasourceSchema_enabled=true
Introduce Segment Schema Publishing and Polling for Efficient Datasource Schema Building (#15817) Issue: #14989 The initial step in optimizing segment metadata was to centralize the construction of datasource schema in the Coordinator (#14985). Thereafter, we addressed the problem of publishing schema for realtime segments (#15475). Subsequently, our goal is to eliminate the requirement for regularly executing queries to obtain segment schema information. This is the final change which involves publishing segment schema for finalized segments from task and periodically polling them in the Coordinator.
2024-04-24 12:52:53 -04:00
- druid_centralizedDatasourceSchema_backFillEnabled=true
- druid_centralizedDatasourceSchema_backFillPeriod=15000
Relocating Table Schema Building: Shifting from Brokers to Coordinator for Improved Efficiency (#14985) In the current design, brokers query both data nodes and tasks to fetch the schema of the segments they serve. The table schema is then constructed by combining the schemas of all segments within a datasource. However, this approach leads to a high number of segment metadata queries during broker startup, resulting in slow startup times and various issues outlined in the design proposal. To address these challenges, we propose centralizing the table schema management process within the coordinator. This change is the first step in that direction. In the new arrangement, the coordinator will take on the responsibility of querying both data nodes and tasks to fetch segment schema and subsequently building the table schema. Brokers will now simply query the Coordinator to fetch table schema. Importantly, brokers will still retain the capability to build table schemas if the need arises, ensuring both flexibility and resilience.
2023-11-04 10:03:25 -04:00
- druid_coordinator_segmentMetadata_metadataRefreshPeriod=PT15S
depends_on:
- druid-overlord
- druid-metadata-storage
- druid-zookeeper-kafka
druid-overlord:
extends:
file: docker-compose.base.yml
service: druid-overlord
environment:
- DRUID_INTEGRATION_TEST_GROUP=${DRUID_INTEGRATION_TEST_GROUP}
Introduce Segment Schema Publishing and Polling for Efficient Datasource Schema Building (#15817) Issue: #14989 The initial step in optimizing segment metadata was to centralize the construction of datasource schema in the Coordinator (#14985). Thereafter, we addressed the problem of publishing schema for realtime segments (#15475). Subsequently, our goal is to eliminate the requirement for regularly executing queries to obtain segment schema information. This is the final change which involves publishing segment schema for finalized segments from task and periodically polling them in the Coordinator.
2024-04-24 12:52:53 -04:00
- druid_centralizedDatasourceSchema_enabled=true
Relocating Table Schema Building: Shifting from Brokers to Coordinator for Improved Efficiency (#14985) In the current design, brokers query both data nodes and tasks to fetch the schema of the segments they serve. The table schema is then constructed by combining the schemas of all segments within a datasource. However, this approach leads to a high number of segment metadata queries during broker startup, resulting in slow startup times and various issues outlined in the design proposal. To address these challenges, we propose centralizing the table schema management process within the coordinator. This change is the first step in that direction. In the new arrangement, the coordinator will take on the responsibility of querying both data nodes and tasks to fetch segment schema and subsequently building the table schema. Brokers will now simply query the Coordinator to fetch table schema. Importantly, brokers will still retain the capability to build table schemas if the need arises, ensuring both flexibility and resilience.
2023-11-04 10:03:25 -04:00
depends_on:
- druid-metadata-storage
- druid-zookeeper-kafka
druid-historical:
extends:
file: docker-compose.base.yml
service: druid-historical
environment:
- DRUID_INTEGRATION_TEST_GROUP=${DRUID_INTEGRATION_TEST_GROUP}
depends_on:
- druid-zookeeper-kafka
druid-middlemanager:
extends:
file: docker-compose.base.yml
service: druid-middlemanager
environment:
- DRUID_INTEGRATION_TEST_GROUP=${DRUID_INTEGRATION_TEST_GROUP}
Introduce Segment Schema Publishing and Polling for Efficient Datasource Schema Building (#15817) Issue: #14989 The initial step in optimizing segment metadata was to centralize the construction of datasource schema in the Coordinator (#14985). Thereafter, we addressed the problem of publishing schema for realtime segments (#15475). Subsequently, our goal is to eliminate the requirement for regularly executing queries to obtain segment schema information. This is the final change which involves publishing segment schema for finalized segments from task and periodically polling them in the Coordinator.
2024-04-24 12:52:53 -04:00
- druid_indexer_fork_property_druid_centralizedDatasourceSchema_enabled=true
Relocating Table Schema Building: Shifting from Brokers to Coordinator for Improved Efficiency (#14985) In the current design, brokers query both data nodes and tasks to fetch the schema of the segments they serve. The table schema is then constructed by combining the schemas of all segments within a datasource. However, this approach leads to a high number of segment metadata queries during broker startup, resulting in slow startup times and various issues outlined in the design proposal. To address these challenges, we propose centralizing the table schema management process within the coordinator. This change is the first step in that direction. In the new arrangement, the coordinator will take on the responsibility of querying both data nodes and tasks to fetch segment schema and subsequently building the table schema. Brokers will now simply query the Coordinator to fetch table schema. Importantly, brokers will still retain the capability to build table schemas if the need arises, ensuring both flexibility and resilience.
2023-11-04 10:03:25 -04:00
depends_on:
- druid-zookeeper-kafka
- druid-overlord
druid-broker:
extends:
file: docker-compose.base.yml
service: druid-broker
environment:
- DRUID_INTEGRATION_TEST_GROUP=${DRUID_INTEGRATION_TEST_GROUP}
- druid_sql_planner_metadataRefreshPeriod=PT20S
- druid_sql_planner_disableSegmentMetadataQueries=true
depends_on:
- druid-coordinator
- druid-zookeeper-kafka
- druid-middlemanager
- druid-historical
druid-router:
extends:
file: docker-compose.base.yml
service: druid-router
environment:
- DRUID_INTEGRATION_TEST_GROUP=${DRUID_INTEGRATION_TEST_GROUP}
depends_on:
- druid-zookeeper-kafka
- druid-coordinator
- druid-broker
- druid-overlord
networks:
druid-it-net:
name: druid-it-net
ipam:
config:
- subnet: 172.172.172.0/24