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Subject [GitHub] [spark] dongjoon-hyun commented on a change in pull request #24851: [SPARK-27303][GRAPH] Add Spark Graph API
Date Fri, 11 Oct 2019 16:13:32 GMT
dongjoon-hyun commented on a change in pull request #24851: [SPARK-27303][GRAPH] Add Spark
Graph API
URL: https://github.com/apache/spark/pull/24851#discussion_r334068831
 
 

 ##########
 File path: graph/api/src/main/scala/org/apache/spark/graph/api/CypherSession.scala
 ##########
 @@ -0,0 +1,258 @@
+/*
+ * 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.spark.graph.api
+
+import scala.collection.JavaConverters._
+
+import org.apache.spark.internal.Logging
+import org.apache.spark.sql.{Dataset, Row, SparkSession}
+import org.apache.spark.sql.types.{BooleanType, StructType}
+
+/**
+ * Contains constants used for convention based column naming.
+ */
+object CypherSession {
+
+  /**
+   * Naming convention for identifier columns, both node and relationship identifiers.
+   */
+  val ID_COLUMN = "$ID"
+
+  /**
+   * Naming convention for relationship source identifier.
+   */
+  val SOURCE_ID_COLUMN = "$SOURCE_ID"
+
+  /**
+   * Naming convention for relationship target identifier.
+   */
+  val TARGET_ID_COLUMN = "$TARGET_ID"
+
+  /**
+   * Naming convention both for node label and relationship type prefixes.
+   */
+  val LABEL_COLUMN_PREFIX = ":"
+}
+
+/**
+ * A CypherSession allows for creating, storing and loading [[PropertyGraph]] instances as
well as
+ * executing Cypher queries on them.
+ *
+ * Wraps a [[org.apache.spark.sql.SparkSession]].
+ *
+ * @since 3.0.0
+ */
+trait CypherSession extends Logging {
+
+  def sparkSession: SparkSession
+
+  /**
+   * Executes a Cypher query on the given input graph.
+   *
+   * @param graph [[PropertyGraph]] on which the query is executed
+   * @param query Cypher query to execute
+   * @since 3.0.0
+   */
+  def cypher(graph: PropertyGraph, query: String): CypherResult
+
+  /**
+   * Executes a Cypher query on the given input graph.
+   *
+   * Note that queries can take optional parameters:
+   *
+   * {{{
+   *     Parameters:
+   *
+   *     {
+   *        "name" : "Alice"
+   *     }
+   *
+   *     Query:
+   *
+   *     MATCH (n:Person)
+   *     WHERE n.name = $name
+   *     RETURN n
+   * }}}
+   *
+   * @param graph      [[PropertyGraph]] on which the query is executed
+   * @param query      Cypher query to execute
+   * @param parameters parameters used by the Cypher query
+   * @since 3.0.0
+   */
+  def cypher(graph: PropertyGraph, query: String, parameters: Map[String, Any]): CypherResult
+
+  /**
+   * Executes a Cypher query on the given input graph.
+   *
+   * Note that queries can take optional parameters:
+   *
+   * {{{
+   *     Parameters:
+   *
+   *     {
+   *        "name" : "Alice"
+   *     }
+   *
+   *     Query:
+   *
+   *     MATCH (n:Person)
+   *     WHERE n.name = $name
+   *     RETURN n
+   * }}}
+   *
+   * @param graph      [[PropertyGraph]] on which the query is executed
+   * @param query      Cypher query to execute
+   * @param parameters parameters used by the Cypher query
+   * @since 3.0.0
+   */
+  def cypher(
+      graph: PropertyGraph,
+      query: String,
+      parameters: java.util.Map[String, Object]): CypherResult = {
+    cypher(graph, query, parameters.asScala.toMap)
+  }
+
+  /**
+   * Creates a [[PropertyGraph]] from a sequence of [[NodeFrame]]s and [[RelationshipFrame]]s.
+   * At least one [[NodeFrame]] has to be provided.
+   *
+   * For each label set and relationship type there can be at most one [[NodeFrame]] and
at most one
+   * [[RelationshipFrame]], respectively.
+   *
+   * @param nodes         NodeFrames that define the nodes in the graph
+   * @param relationships RelationshipFrames that define the relationships in the graph
+   * @since 3.0.0
+   */
+  def createGraph(nodes: Array[NodeFrame], relationships: Array[RelationshipFrame]): PropertyGraph
+
+  /**
+   * Creates a [[PropertyGraph]] from nodes and relationships.
+   *
+   * The given dataset needs to adhere to the following column naming conventions:
+   *
+   * {{{
+   *     Id column:        `$ID`            (nodes and relationships)
+   *     SourceId column:  `$SOURCE_ID`     (relationships)
+   *     TargetId column:  `$TARGET_ID`     (relationships)
+   *
+   *     Label columns:    `:{LABEL_NAME}`  (nodes)
+   *     RelType columns:  `:{REL_TYPE}`    (relationships)
+   *
+   *     Property columns: `{Property_Key}` (nodes and relationships)
+   * }}}
+   *
+   * @note It is recommended to cache the input datasets if they represent multiple label
sets and
+   *       relationship types.
+   *
+   * @see [[CypherSession]]
+   * @param nodes         node dataset
+   * @param relationships relationship dataset
+   * @since 3.0.0
+   */
+  def createGraph(nodes: Dataset[Row], relationships: Dataset[Row]): PropertyGraph = {
 
 Review comment:
   That is not the main reason to ask this. The logic is really helper logic. We had better
move that out to this `trait`.

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