feat(backend):spark calc fix

backend/src/main/java/io/dataease/service/chart/ChartViewService.java

@@ -119,7 +119,8 @@ public class ChartViewService {
             data = datasourceProvider.getData(datasourceRequest);
         } else if (table.getMode() == 1) {// 抽取
             DataTableInfoDTO dataTableInfoDTO = new Gson().fromJson(table.getInfo(), DataTableInfoDTO.class);
-            data = sparkCalc.getData(dataTableInfoDTO.getTable() + "-" + table.getDataSourceId(), xAxis, yAxis, "tmp");// todo hBase table name maybe change
+            String tableName = dataTableInfoDTO.getTable() + "-" + table.getDataSourceId();// todo hBase table name maybe change
+            data = sparkCalc.getData(tableName, xAxis, yAxis, view.getId().split("-")[0]);
         }
 
         // 图表组件可再扩展

backend/src/main/java/io/dataease/service/spark/SparkCalc.java

@@ -16,16 +16,15 @@ import org.apache.spark.api.java.JavaPairRDD;
 import org.apache.spark.api.java.JavaRDD;
 import org.apache.spark.api.java.JavaSparkContext;
 import org.apache.spark.api.java.function.FlatMapFunction;
-import org.apache.spark.sql.Dataset;
-import org.apache.spark.sql.Row;
-import org.apache.spark.sql.RowFactory;
-import org.apache.spark.sql.SQLContext;
+import org.apache.spark.sql.*;
 import org.apache.spark.sql.types.DataTypes;
 import org.apache.spark.sql.types.StructField;
 import org.apache.spark.sql.types.StructType;
+import org.springframework.core.env.Environment;
 import org.springframework.stereotype.Service;
 import scala.Tuple2;
 
+import javax.annotation.Resource;
 import java.text.MessageFormat;
 import java.util.ArrayList;
 import java.util.Base64;
@@ -39,6 +38,8 @@ import java.util.List;
 @Service
 public class SparkCalc {
     private static String column_family = "dataease";
+    @Resource
+    private Environment env; // 保存了配置文件的信息
 
     public List<String[]> getData(String hTable, List<ChartViewFieldDTO> xAxis, List<ChartViewFieldDTO> yAxis, String tmpTable) throws Exception {
         Scan scan = new Scan();
@@ -46,8 +47,21 @@ public class SparkCalc {
         ClientProtos.Scan proto = ProtobufUtil.toScan(scan);
         String scanToString = new String(Base64.getEncoder().encode(proto.toByteArray()));
 
-        JavaSparkContext sparkContext = CommonBeanFactory.getBean(JavaSparkContext.class);
-        Configuration conf = CommonBeanFactory.getBean(Configuration.class);
+        // Spark Context
+//        JavaSparkContext sparkContext = CommonBeanFactory.getBean(JavaSparkContext.class);
+        SparkSession spark = SparkSession.builder()
+                .appName(env.getProperty("spark.appName", "DataeaseJob"))
+                .master(env.getProperty("spark.master", "local[*]"))
+                .config("spark.scheduler.mode", "FAIR")
+                .getOrCreate();
+        JavaSparkContext sparkContext = new JavaSparkContext(spark.sparkContext());
+
+        // HBase config
+//        Configuration conf = CommonBeanFactory.getBean(Configuration.class);
+        org.apache.hadoop.conf.Configuration conf = new org.apache.hadoop.conf.Configuration();
+        conf.set("hbase.zookeeper.quorum", env.getProperty("hbase.zookeeper.quorum"));
+        conf.set("hbase.zookeeper.property.clientPort", env.getProperty("hbase.zookeeper.property.clientPort"));
+        conf.set("hbase.client.retries.number", env.getProperty("hbase.client.retries.number", "1"));
         conf.set(TableInputFormat.INPUT_TABLE, hTable);
         conf.set(TableInputFormat.SCAN, scanToString);
 
@@ -103,12 +117,15 @@ public class SparkCalc {
         });
         StructType structType = DataTypes.createStructType(structFields);
 
-        SQLContext sqlContext = CommonBeanFactory.getBean(SQLContext.class);
+        // Spark SQL Context
+//        SQLContext sqlContext = CommonBeanFactory.getBean(SQLContext.class);
+        SQLContext sqlContext = new SQLContext(sparkContext);
+        sqlContext.setConf("spark.sql.shuffle.partitions", env.getProperty("spark.sql.shuffle.partitions", "1"));
+        sqlContext.setConf("spark.default.parallelism", env.getProperty("spark.default.parallelism", "1"));
+
         Dataset<Row> dataFrame = sqlContext.createDataFrame(rdd, structType);
         dataFrame.createOrReplaceTempView(tmpTable);
-
         Dataset<Row> sql = sqlContext.sql(getSQL(xAxis, yAxis, tmpTable));
-
         // transform
         List<String[]> data = new ArrayList<>();
         List<Row> list = sql.collectAsList();
@@ -119,7 +136,6 @@ public class SparkCalc {
             }
             data.add(r);
         }
-
         return data;
     }