[GitHub] [spark] s1ck commented on a change in pull request #24851: [SPARK-27303][GRAPH] Add Spark Graph API

[GitBox <gi...@apache.org>]

s1ck commented on a change in pull request #24851: [SPARK-27303][GRAPH] Add Spark Graph API
URL: https://github.com/apache/spark/pull/24851#discussion_r307224806
 
 

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 File path: graph/api/src/main/scala/org/apache/spark/graph/api/CypherSession.scala
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 @@ -0,0 +1,138 @@
+/*
+ * 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.sql.{functions, DataFrame, SparkSession}
+
+object CypherSession {
+  val ID_COLUMN = "$ID"
+  val SOURCE_ID_COLUMN = "$SOURCE_ID"
+  val TARGET_ID_COLUMN = "$TARGET_ID"
+  val LABEL_COLUMN_PREFIX = ":"
+}
+
+/**
+ * The entry point for using property graphs in Spark.
+ *
+ * Provides factory methods for creating [[PropertyGraph]] instances.
+ *
+ * Wraps a [[org.apache.spark.sql.SparkSession]].
+ *
+ * @since 3.0.0
+ */
+trait CypherSession {
+
+  def sparkSession: SparkSession
+
+  /**
+   * Creates a [[PropertyGraph]] from a sequence of [[NodeFrame]]s and [[RelationshipFrame]]s.
+   * At least one [[NodeFrame]] has to be provided.
+   *
+   * For each label set and relationship type there can be at most one [[NodeFrame]] and at most one
+   * [[RelationshipFrame]], respectively.
+   *
+   * @param nodes         NodeFrames that define the nodes in the graph
+   * @param relationships RelationshipFrames that define the relationships in the graph
+   * @since 3.0.0
+   */
+  def createGraph(nodes: Seq[NodeFrame], relationships: Seq[RelationshipFrame]): PropertyGraph
+
+  /**
+   * Creates a [[PropertyGraph]] from a sequence of [[NodeFrame]]s and [[RelationshipFrame]]s.
+   * At least one [[NodeFrame]] has to be provided.
+   *
+   * For each label set and relationship type there can be at most one [[NodeFrame]] and at most one
+   * [[RelationshipFrame]], respectively.
+   *
+   * @param nodes         NodeFrames that define the nodes in the graph
+   * @param relationships RelationshipFrames that define the relationships in the graph
+   * @since 3.0.0
+   */
+  def createGraph(
+      nodes: java.util.List[NodeFrame],
+      relationships: java.util.List[RelationshipFrame]): PropertyGraph = {
+    createGraph(JavaConverters.asScalaBuffer(nodes), JavaConverters.asScalaBuffer(relationships))
+  }
+
+  /**
+   * Creates a [[PropertyGraph]] from nodes and relationships.
+   *
+   * The given DataFrames need to adhere to the following column naming conventions:
+   *
+   * {{{
+   *     Id column:        `$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)
+   * }}}
+   *
+   * @see [[CypherSession]]
+   * @param nodes         node DataFrame
+   * @param relationships relationship DataFrame
+   * @since 3.0.0
+   */
+  def createGraph(nodes: DataFrame, relationships: DataFrame): PropertyGraph = {
+    val idColumn = CypherSession.ID_COLUMN
+    val sourceIdColumn = CypherSession.SOURCE_ID_COLUMN
+    val targetIdColumn = CypherSession.TARGET_ID_COLUMN
+
+    val labelColumns = nodes.columns.filter(_.startsWith(CypherSession.LABEL_COLUMN_PREFIX)).toSet
+    val nodeProperties = (nodes.columns.toSet - idColumn -- labelColumns)
+      .map(col => col -> col)
+      .toMap
+
+    val trueLit = functions.lit(true)
+    val falseLit = functions.lit(false)
+
+    val labelSets = labelColumns.subsets().toSet + Set.empty
 
 Review comment:
   I created https://issues.apache.org/jira/browse/SPARK-28513

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