Examples with ComputedColumn org.apache.flink.table.api.TableColumn.ComputedColumn used on opensource projects

Example 1 with ComputedColumn

use of org.apache.flink.table.api.TableColumn.ComputedColumn in project flink by apache.

the class DescriptorProperties method putTableSchema.

/**
 * Adds a table schema under the given key.
 */
public void putTableSchema(String key, TableSchema schema) {
    checkNotNull(key);
    checkNotNull(schema);
    final String[] fieldNames = schema.getFieldNames();
    final DataType[] fieldTypes = schema.getFieldDataTypes();
    final String[] fieldExpressions = schema.getTableColumns().stream().map(column -> {
        if (column instanceof ComputedColumn) {
            return ((ComputedColumn) column).getExpression();
        }
        return null;
    }).toArray(String[]::new);
    final String[] fieldMetadata = schema.getTableColumns().stream().map(column -> {
        if (column instanceof MetadataColumn) {
            return ((MetadataColumn) column).getMetadataAlias().orElse(column.getName());
        }
        return null;
    }).toArray(String[]::new);
    final String[] fieldVirtual = schema.getTableColumns().stream().map(column -> {
        if (column instanceof MetadataColumn) {
            return Boolean.toString(((MetadataColumn) column).isVirtual());
        }
        return null;
    }).toArray(String[]::new);
    final List<List<String>> values = new ArrayList<>();
    for (int i = 0; i < schema.getFieldCount(); i++) {
        values.add(Arrays.asList(fieldNames[i], fieldTypes[i].getLogicalType().asSerializableString(), fieldExpressions[i], fieldMetadata[i], fieldVirtual[i]));
    }
    putIndexedOptionalProperties(key, Arrays.asList(NAME, DATA_TYPE, EXPR, METADATA, VIRTUAL), values);
    if (!schema.getWatermarkSpecs().isEmpty()) {
        final List<List<String>> watermarkValues = new ArrayList<>();
        for (WatermarkSpec spec : schema.getWatermarkSpecs()) {
            watermarkValues.add(Arrays.asList(spec.getRowtimeAttribute(), spec.getWatermarkExpr(), spec.getWatermarkExprOutputType().getLogicalType().asSerializableString()));
        }
        putIndexedFixedProperties(key + '.' + WATERMARK, Arrays.asList(WATERMARK_ROWTIME, WATERMARK_STRATEGY_EXPR, WATERMARK_STRATEGY_DATA_TYPE), watermarkValues);
    }
    schema.getPrimaryKey().ifPresent(pk -> {
        putString(key + '.' + PRIMARY_KEY_NAME, pk.getName());
        putString(key + '.' + PRIMARY_KEY_COLUMNS, String.join(",", pk.getColumns()));
    });
}

Example 2 with ComputedColumn

use of org.apache.flink.table.api.TableColumn.ComputedColumn in project flink by apache.

the class SqlToOperationConverterTest method testCreateTableWithComputedColumn.

@Test
public void testCreateTableWithComputedColumn() {
    final String sql = "CREATE TABLE tbl1 (\n" + "  a int,\n" + "  b varchar, \n" + "  c as a - 1, \n" + "  d as b || '$$', \n" + "  e as my_udf1(a)," + "  f as `default`.my_udf2(a) + 1," + "  g as builtin.`default`.my_udf3(a) || '##'\n" + ")\n" + "  with (\n" + "    'connector' = 'kafka', \n" + "    'kafka.topic' = 'log.test'\n" + ")\n";
    functionCatalog.registerTempCatalogScalarFunction(ObjectIdentifier.of("builtin", "default", "my_udf1"), Func0$.MODULE$);
    functionCatalog.registerTempCatalogScalarFunction(ObjectIdentifier.of("builtin", "default", "my_udf2"), Func1$.MODULE$);
    functionCatalog.registerTempCatalogScalarFunction(ObjectIdentifier.of("builtin", "default", "my_udf3"), Func8$.MODULE$);
    FlinkPlannerImpl planner = getPlannerBySqlDialect(SqlDialect.DEFAULT);
    Operation operation = parse(sql, planner, getParserBySqlDialect(SqlDialect.DEFAULT));
    assertThat(operation).isInstanceOf(CreateTableOperation.class);
    CreateTableOperation op = (CreateTableOperation) operation;
    CatalogTable catalogTable = op.getCatalogTable();
    assertThat(catalogTable.getSchema().getFieldNames()).isEqualTo(new String[] { "a", "b", "c", "d", "e", "f", "g" });
    assertThat(catalogTable.getSchema().getFieldDataTypes()).isEqualTo(new DataType[] { DataTypes.INT(), DataTypes.STRING(), DataTypes.INT(), DataTypes.STRING(), DataTypes.INT().notNull(), DataTypes.INT(), DataTypes.STRING() });
    String[] columnExpressions = catalogTable.getSchema().getTableColumns().stream().filter(ComputedColumn.class::isInstance).map(ComputedColumn.class::cast).map(ComputedColumn::getExpression).toArray(String[]::new);
    String[] expected = new String[] { "`a` - 1", "`b` || '$$'", "`builtin`.`default`.`my_udf1`(`a`)", "`builtin`.`default`.`my_udf2`(`a`) + 1", "`builtin`.`default`.`my_udf3`(`a`) || '##'" };
    assertThat(columnExpressions).isEqualTo(expected);
}

Example 3 with ComputedColumn

use of org.apache.flink.table.api.TableColumn.ComputedColumn in project flink by apache.

the class TableSchema method toSchema.

/**
 * Helps to migrate to the new {@link Schema} class.
 */
public Schema toSchema() {
    final Schema.Builder builder = Schema.newBuilder();
    columns.forEach(column -> {
        if (column instanceof PhysicalColumn) {
            final PhysicalColumn c = (PhysicalColumn) column;
            builder.column(c.getName(), c.getType());
        } else if (column instanceof MetadataColumn) {
            final MetadataColumn c = (MetadataColumn) column;
            builder.columnByMetadata(c.getName(), c.getType(), c.getMetadataAlias().orElse(null), c.isVirtual());
        } else if (column instanceof ComputedColumn) {
            final ComputedColumn c = (ComputedColumn) column;
            builder.columnByExpression(c.getName(), c.getExpression());
        } else {
            throw new IllegalArgumentException("Unsupported column type: " + column);
        }
    });
    watermarkSpecs.forEach(spec -> builder.watermark(spec.getRowtimeAttribute(), spec.getWatermarkExpr()));
    if (primaryKey != null) {
        builder.primaryKeyNamed(primaryKey.getName(), primaryKey.getColumns());
    }
    return builder.build();
}