[BugFix][Spark] Fix the bug that VertexWrite does not generate vertex count file

spark/src/main/scala/com/alibaba/graphar/reader/VertexReader.scala

@@ -18,8 +18,8 @@ package com.alibaba.graphar.reader
 import com.alibaba.graphar.utils.{IndexGenerator, DataFrameConcat}
 import com.alibaba.graphar.{GeneralParams, VertexInfo, FileType, PropertyGroup}
 import com.alibaba.graphar.datasources._
+import com.alibaba.graphar.utils.FileSystem
 
-import org.apache.hadoop.fs.{Path, FileSystem}
 import org.apache.spark.sql.{DataFrame, SparkSession}
 import org.apache.spark.sql.types._
 import org.apache.spark.sql.functions._
@@ -36,11 +36,7 @@ class VertexReader(prefix: String, vertexInfo: VertexInfo, spark: SparkSession)
   /** Load the total number of vertices for this vertex type. */
   def readVerticesNumber(): Long = {
     val file_path = prefix + "/" + vertexInfo.getVerticesNumFilePath()
-    val path = new Path(file_path)
-    val file_system = FileSystem.get(path.toUri(), spark.sparkContext.hadoopConfiguration)
-    val input = file_system.open(path)
-    val number = java.lang.Long.reverseBytes(input.readLong())
-    file_system.close()
+    val number = FileSystem.readValue(file_path, spark.sparkContext.hadoopConfiguration)
     return number
   }
 

spark/src/main/scala/com/alibaba/graphar/utils/FileSystem.scala

@@ -68,7 +68,18 @@ object FileSystem {
     val path = new Path(outputPath)
     val fs = path.getFileSystem(hadoopConfig)
     val output = fs.create(path, true)  // create or overwrite
-    output.writeLong(value)
+    // consistent with c++ library, convert to little-endian
+    output.writeLong(java.lang.Long.reverseBytes(value))
     output.close()
   }
+
+  def readValue(inputPath: String, hadoopConfig: Configuration): Long = {
+    val path = new Path(inputPath)
+    val fs = path.getFileSystem(hadoopConfig)
+    val input = fs.open(path)
+    // consistent with c++ library, little-endian in file, convert to big-endian
+    val num = java.lang.Long.reverseBytes(input.readLong())
+    fs.close()
+    return num
+  }
 }

spark/src/main/scala/com/alibaba/graphar/writer/VertexWriter.scala

@@ -60,6 +60,7 @@ class VertexWriter(prefix: String, vertexInfo: VertexInfo, vertexDf: DataFrame,
     case None => vertexDf.count()
     case _ => numVertices.get
   }
+  writeVertexNum()
 
   private var chunks:DataFrame = VertexWriter.repartitionAndSort(vertexDf, vertexInfo.getChunk_size(), vertexNum)
 

spark/src/test/scala/com/alibaba/graphar/TestWriter.scala

@@ -15,8 +15,8 @@
 
 package com.alibaba.graphar
 
-import com.alibaba.graphar.utils.IndexGenerator
 import com.alibaba.graphar.writer.{VertexWriter, EdgeWriter}
+import com.alibaba.graphar.utils
 
 import org.apache.spark.sql.{DataFrame, SparkSession}
 import org.scalatest.funsuite.AnyFunSuite
@@ -45,7 +45,7 @@ class WriterSuite extends AnyFunSuite {
     val vertex_info = vertex_yaml.load(vertex_input).asInstanceOf[VertexInfo]
 
     // generate vertex index column for vertex dataframe
-    val vertex_df_with_index = IndexGenerator.generateVertexIndexColumn(vertex_df)
+    val vertex_df_with_index = utils.IndexGenerator.generateVertexIndexColumn(vertex_df)
 
     // create writer object for person and generate the properties with GAR format
     val prefix : String = "/tmp/"
@@ -61,6 +61,9 @@ class WriterSuite extends AnyFunSuite {
     val chunk_path = new Path(prefix + vertex_info.getPrefix() + "*/*")
     val chunk_files = fs.globStatus(chunk_path)
     assert(chunk_files.length == 20)
+    val vertex_num_path = prefix + vertex_info.getVerticesNumFilePath()
+    val number = utils.FileSystem.readValue(vertex_num_path, spark.sparkContext.hadoopConfiguration)
+    assert(number.toInt == vertex_df.count())
 
     assertThrows[IllegalArgumentException](new VertexWriter(prefix, vertex_info, vertex_df))
     val invalid_property_group= new PropertyGroup()
@@ -89,7 +92,7 @@ class WriterSuite extends AnyFunSuite {
     val srcDf = edge_df.select("src").withColumnRenamed("src", "vertex")
     val dstDf = edge_df.select("dst").withColumnRenamed("dst", "vertex")
     val vertexNum = srcDf.union(dstDf).distinct().count()
-    val edge_df_with_index = IndexGenerator.generateSrcAndDstIndexUnitedlyForEdges(edge_df, "src", "dst")
+    val edge_df_with_index = utils.IndexGenerator.generateSrcAndDstIndexUnitedlyForEdges(edge_df, "src", "dst")
 
     // create writer object for person_knows_person and generate the adj list and properties with GAR format
     val writer = new EdgeWriter(prefix, edge_info, adj_list_type, vertexNum, edge_df_with_index)
@@ -156,10 +159,10 @@ class WriterSuite extends AnyFunSuite {
     val edge_info = edge_yaml.load(edge_input).asInstanceOf[EdgeInfo]
 
     // construct person vertex mapping with dataframe
-    val vertex_mapping = IndexGenerator.constructVertexIndexMapping(vertex_df, vertex_info.getPrimaryKey())
+    val vertex_mapping = utils.IndexGenerator.constructVertexIndexMapping(vertex_df, vertex_info.getPrimaryKey())
     // generate src index and dst index for edge datafram with vertex mapping
-    val edge_df_with_src_index = IndexGenerator.generateSrcIndexForEdgesFromMapping(edge_df, "src", vertex_mapping)
-    val edge_df_with_src_dst_index = IndexGenerator.generateDstIndexForEdgesFromMapping(edge_df_with_src_index, "dst", vertex_mapping)
+    val edge_df_with_src_index = utils.IndexGenerator.generateSrcIndexForEdgesFromMapping(edge_df, "src", vertex_mapping)
+    val edge_df_with_src_dst_index = utils.IndexGenerator.generateDstIndexForEdgesFromMapping(edge_df_with_src_index, "dst", vertex_mapping)
 
     // create writer object for person_knows_person and generate the adj list and properties with GAR format
     val writer = new EdgeWriter(prefix, edge_info, adj_list_type, vertex_num, edge_df_with_src_dst_index)