Java 类名:com.alibaba.alink.operator.batch.sql.FilterBatchOp
Python 类名:FilterBatchOp
对批式数据进行sql的FILTER操作。
名称 | 中文名称 | 描述 | 类型 | 是否必须? | 取值范围 | 默认值 |
---|---|---|---|---|---|---|
clause | 运算语句 | 运算语句 | String | ✓ |
from pyalink.alink import * import pandas as pd useLocalEnv(1) df = pd.DataFrame([ ['Ohio', 2000, 1.5], ['Ohio', 2001, 1.7], ['Ohio', 2002, 3.6], ['Nevada', 2001, 2.4], ['Nevada', 2002, 2.9], ['Nevada', 2003, 3.2] ]) batch_data = BatchOperator.fromDataframe(df, schemaStr='f1 string, f2 bigint, f3 double') op = FilterBatchOp().setClause("f1='Ohio'") batch_data = batch_data.link(op) batch_data.print()
import org.apache.flink.types.Row; import com.alibaba.alink.operator.batch.BatchOperator; import com.alibaba.alink.operator.batch.source.MemSourceBatchOp; import com.alibaba.alink.operator.batch.sql.FilterBatchOp; import org.junit.Test; import java.util.Arrays; import java.util.List; public class FilterBatchOpTest { @Test public void testFilterBatchOp() throws Exception { List <Row> df = Arrays.asList( Row.of("Ohio", 2000, 1.5), Row.of("Ohio", 2001, 1.7), Row.of("Ohio", 2002, 3.6), Row.of("Nevada", 2001, 2.4), Row.of("Nevada", 2002, 2.9), Row.of("Nevada", 2003, 3.2) ); BatchOperator <?> batch_data = new MemSourceBatchOp(df, "f1 string, f2 int, f3 double"); BatchOperator <?> op = new FilterBatchOp().setClause("f1='Ohio'"); batch_data = batch_data.link(op); batch_data.print(); } }
f1 | f2 | f3 |
---|---|---|
Ohio | 2000 | 1.5000 |
Ohio | 2001 | 1.7000 |
Ohio | 2002 | 3.6000 |