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Posted to commits@druid.apache.org by GitBox <gi...@apache.org> on 2021/07/22 19:03:35 UTC
[GitHub] [druid] samarthjain commented on a change in pull request #11474: Set up, confs, mixins, and clients.
samarthjain commented on a change in pull request #11474:
URL: https://github.com/apache/druid/pull/11474#discussion_r675051613
##########
File path: spark/src/main/scala/org/apache/druid/spark/clients/DruidClient.scala
##########
@@ -0,0 +1,197 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with 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.
+ */
+
+package org.apache.druid.spark.clients
+
+import com.fasterxml.jackson.core.`type`.TypeReference
+import com.google.common.net.HostAndPort
+import org.apache.druid.java.util.common.{ISE, Intervals, JodaUtils, StringUtils}
+import org.apache.druid.java.util.http.client.response.{StringFullResponseHandler,
+ StringFullResponseHolder}
+import org.apache.druid.java.util.http.client.{HttpClient, Request}
+import org.apache.druid.query.Druids
+import org.apache.druid.query.metadata.metadata.{ColumnAnalysis, SegmentAnalysis,
+ SegmentMetadataQuery}
+import org.apache.druid.spark.MAPPER
+import org.apache.druid.spark.configuration.{Configuration, DruidConfigurationKeys}
+import org.apache.druid.spark.mixins.Logging
+import org.jboss.netty.handler.codec.http.{HttpMethod, HttpResponseStatus}
+import org.joda.time.{Duration, Interval}
+
+import java.net.URL
+import java.util.{List => JList}
+import javax.ws.rs.core.MediaType
+import scala.collection.JavaConverters.{asScalaBufferConverter, mapAsJavaMapConverter,
+ mapAsScalaMapConverter, seqAsJavaListConverter}
+
+/**
+ * Going with SegmentMetadataQueries despite the significant overhead because there's no other way
+ * to get accurate information about Druid columns.
+ *
+ * This is pulled pretty directly from the druid-hadoop-input-format project on GitHub. There is
+ * likely substantial room for improvement.
+ */
+class DruidClient(
+ httpClient: HttpClient,
+ hostAndPort: HostAndPort,
+ numRetries: Int,
+ retryWaitSeconds: Int,
+ timeoutWaitMilliseconds: Int
+ ) extends Logging {
+ private val druidBaseQueryURL: HostAndPort => String =
+ (hostAndPort: HostAndPort) => s"http://$hostAndPort/druid/v2/"
+
+ private val DefaultSegmentMetadataInterval = List[Interval](Intervals.utc(
+ JodaUtils.MIN_INSTANT,
+ JodaUtils.MAX_INSTANT
+ ))
+
+ /**
+ * The SQL system catalog tables are incorrect for multivalue columns and don't have accurate
+ * type info, so we need to fall back to segmentMetadataQueries. Given a DATASOURCE and a range
+ * of INTERVALS to query over, return a map from column name to a tuple of
+ * (columnType, hasMultipleValues). Note that this is a very expensive operation over large
+ * numbers of segments. If possible, this method should only be called with the most granular
+ * starting and ending intervals instead of over a larger interval.
+ *
+ * @param dataSource The Druid dataSource to fetch the schema for.
+ * @param intervals The intervals to return the schema for, or None to query all segments.
+ * @return A map from column name to data type and whether or not the column is multi-value
+ * for the schema of DATASOURCE.
+ */
+ def getSchema(dataSource: String, intervals: Option[List[Interval]]): Map[String, (String, Boolean)] = {
+ val queryInterval = intervals.getOrElse(DefaultSegmentMetadataInterval)
+ val body = Druids.newSegmentMetadataQueryBuilder()
+ .dataSource(dataSource)
+ .intervals(queryInterval.asJava)
+ .analysisTypes(SegmentMetadataQuery.AnalysisType.SIZE)
+ .merge(true)
+ .context(Map[String, AnyRef](
+ "timeout" -> Int.box(timeoutWaitMilliseconds)
+ ).asJava)
+ .build()
+ val response = sendRequestWithRetry(
+ druidBaseQueryURL(hostAndPort), numRetries, Option(MAPPER.writeValueAsBytes(body))
+ )
+ val segments =
+ MAPPER.readValue[JList[SegmentAnalysis]](
+ response.getContent, new TypeReference[JList[SegmentAnalysis]]() {})
+ if (segments.size() == 0) {
+ throw new ISE(
Review comment:
Nit: This probably should be an `IllegalArgumentException` since `intervals` and `dataSource` are passed as arguments.
##########
File path: spark/src/main/scala/org/apache/druid/spark/mixins/Logging.scala
##########
@@ -0,0 +1,123 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with 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.
+ */
+
+package org.apache.druid.spark.mixins
+
+import org.slf4j.{Logger, LoggerFactory}
+
+/**
+ * Simplified version of org.apache.spark.internal.Logging.
+ */
+trait Logging {
Review comment:
Is there a reason why we can't use `org.apache.druid.java.util.common.logger.Logger` class?
##########
File path: spark/src/main/scala/org/apache/druid/spark/clients/DruidClient.scala
##########
@@ -0,0 +1,197 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with 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.
+ */
+
+package org.apache.druid.spark.clients
+
+import com.fasterxml.jackson.core.`type`.TypeReference
+import com.google.common.net.HostAndPort
+import org.apache.druid.java.util.common.{ISE, Intervals, JodaUtils, StringUtils}
+import org.apache.druid.java.util.http.client.response.{StringFullResponseHandler,
+ StringFullResponseHolder}
+import org.apache.druid.java.util.http.client.{HttpClient, Request}
+import org.apache.druid.query.Druids
+import org.apache.druid.query.metadata.metadata.{ColumnAnalysis, SegmentAnalysis,
+ SegmentMetadataQuery}
+import org.apache.druid.spark.MAPPER
+import org.apache.druid.spark.configuration.{Configuration, DruidConfigurationKeys}
+import org.apache.druid.spark.mixins.Logging
+import org.jboss.netty.handler.codec.http.{HttpMethod, HttpResponseStatus}
+import org.joda.time.{Duration, Interval}
+
+import java.net.URL
+import java.util.{List => JList}
+import javax.ws.rs.core.MediaType
+import scala.collection.JavaConverters.{asScalaBufferConverter, mapAsJavaMapConverter,
+ mapAsScalaMapConverter, seqAsJavaListConverter}
+
+/**
+ * Going with SegmentMetadataQueries despite the significant overhead because there's no other way
+ * to get accurate information about Druid columns.
+ *
+ * This is pulled pretty directly from the druid-hadoop-input-format project on GitHub. There is
+ * likely substantial room for improvement.
+ */
+class DruidClient(
+ httpClient: HttpClient,
+ hostAndPort: HostAndPort,
+ numRetries: Int,
+ retryWaitSeconds: Int,
+ timeoutWaitMilliseconds: Int
+ ) extends Logging {
+ private val druidBaseQueryURL: HostAndPort => String =
+ (hostAndPort: HostAndPort) => s"http://$hostAndPort/druid/v2/"
+
+ private val DefaultSegmentMetadataInterval = List[Interval](Intervals.utc(
+ JodaUtils.MIN_INSTANT,
+ JodaUtils.MAX_INSTANT
+ ))
+
+ /**
+ * The SQL system catalog tables are incorrect for multivalue columns and don't have accurate
+ * type info, so we need to fall back to segmentMetadataQueries. Given a DATASOURCE and a range
+ * of INTERVALS to query over, return a map from column name to a tuple of
+ * (columnType, hasMultipleValues). Note that this is a very expensive operation over large
+ * numbers of segments. If possible, this method should only be called with the most granular
+ * starting and ending intervals instead of over a larger interval.
+ *
+ * @param dataSource The Druid dataSource to fetch the schema for.
+ * @param intervals The intervals to return the schema for, or None to query all segments.
+ * @return A map from column name to data type and whether or not the column is multi-value
+ * for the schema of DATASOURCE.
+ */
+ def getSchema(dataSource: String, intervals: Option[List[Interval]]): Map[String, (String, Boolean)] = {
+ val queryInterval = intervals.getOrElse(DefaultSegmentMetadataInterval)
+ val body = Druids.newSegmentMetadataQueryBuilder()
+ .dataSource(dataSource)
+ .intervals(queryInterval.asJava)
+ .analysisTypes(SegmentMetadataQuery.AnalysisType.SIZE)
+ .merge(true)
+ .context(Map[String, AnyRef](
+ "timeout" -> Int.box(timeoutWaitMilliseconds)
+ ).asJava)
+ .build()
+ val response = sendRequestWithRetry(
+ druidBaseQueryURL(hostAndPort), numRetries, Option(MAPPER.writeValueAsBytes(body))
+ )
+ val segments =
+ MAPPER.readValue[JList[SegmentAnalysis]](
+ response.getContent, new TypeReference[JList[SegmentAnalysis]]() {})
+ if (segments.size() == 0) {
+ throw new ISE(
+ s"No segments found for intervals [${intervals.mkString(",")}] on $dataSource"
+ )
+ }
+ // Since we're setting merge to true, there should only be one item in the list
+ if (segments.size() > 1) {
+ throw new ISE("Merged segment metadata response had more than one row!")
+ }
+ log.debug(segments.asScala.map(_.toString).mkString("SegmentAnalysis: [", ", ", "]"))
Review comment:
Is `segments.asScala.map(_.toString).mkString("SegmentAnalysis: [", ", ", "]")` evaluated eagerly? If so, this could be an expensive operation. Maybe make this lazy using formatArgs `public void debug(String message, Object... formatArgs)` or check `log.isDebugEnabled()` before calling log.debug (which does the same check again but shouldn't be a big deal).
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