Java 类名:com.alibaba.alink.operator.batch.sql.UnionBatchOp
Python 类名:UnionBatchOp
对批式数据进行sql的UNION操作(去重)。
名称 | 中文名称 | 描述 | 类型 | 是否必须? | 取值范围 | 默认值 |
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from pyalink.alink import * import pandas as pd useLocalEnv(1) df1 = pd.DataFrame([ ['Ohio', 2000, 1.5], ['Ohio', 2000, 1.5], ['Ohio', 2002, 3.6], ['Nevada', 2001, 2.4], ['Nevada', 2002, 2.9], ['Nevada', 2003, 3.2] ]) df2 = pd.DataFrame([ ['Nevada', 2001, 2.4], ['Nevada', 2003, 3.2] ]) batch_data1 = BatchOperator.fromDataframe(df1, schemaStr='f1 string, f2 bigint, f3 double') batch_data2 = BatchOperator.fromDataframe(df2, schemaStr='f1 string, f2 bigint, f3 double') UnionBatchOp().linkFrom(batch_data1, batch_data2).print()
import com.alibaba.alink.operator.batch.BatchOperator; import com.alibaba.alink.operator.batch.source.CsvSourceBatchOp; import com.alibaba.alink.operator.batch.sql.UnionBatchOp; import org.junit.Test; public class UnionBatchOpTest { @Test public void testUnionBatchOp() throws Exception { List <Row> df1 = Arrays.asList( Row.of("Ohio", 2000, 1.5), Row.of("Ohio", 2000, 1.5), Row.of("Ohio", 2002, 3.6), Row.of("Nevada", 2001, 2.4), Row.of("Nevada", 2002, 2.9), Row.of("Nevada", 2003, 3.2) ); List <Row> df2 = Arrays.asList( Row.of("Nevada", 2001, 2.4), Row.of("Nevada", 2003, 3.2) ); BatchOperator <?> data1 = new MemSourceBatchOp(df1, "f1 string, f2 int, f3 double"); BatchOperator <?> data2 = new MemSourceBatchOp(df2, "f1 string, f2 int, f3 double"); BatchOperator <?> union = new UnionBatchOp(); union.linkFrom(data1, data2).print(); } }
f1 | f2 | f3 |
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Nevada | 2001 | 2.4000 |
Nevada | 2002 | 2.9000 |
Nevada | 2003 | 3.2000 |
Ohio | 2000 | 1.5000 |
Ohio | 2002 | 3.6000 |