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| http://www.sohu.com/a/131128039_505813 | |
| 电商后台设计 | |
| 本文包括以下几个部分: | |
| 电商后台系统概述 | |
| 电商后台产品设计:商品中心 | |
| 电商后台产品设计:订单拆单 | |
| 电商后台产品设计:促销活动解析 | |
| 电商后台产品设计:优惠券的设计和妙用 |
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| /** | |
| * It lookup the correct datasource to use, we have one per tenant | |
| * | |
| * The tenant datasource has default properties from database.properties and | |
| * also properties in database.{tenantId}.properties whose properties override | |
| * the default ones. | |
| * | |
| * @author jose.mgmaestre | |
| * | |
| */ |
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| /** | |
| * It specify what Tenant should be use when the hibernate session is created. | |
| * @author jm | |
| */ | |
| public class CurrentTenantIdentifierResolverImpl implements CurrentTenantIdentifierResolver { | |
| Logger logger = Logger.getLogger(getClass()); | |
| @Override |
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| /** | |
| * It gets the connection based on different datasources. | |
| */ | |
| public class MultiTenantConnectionProviderImpl extends AbstractDataSourceBasedMultiTenantConnectionProviderImpl | |
| { | |
| Log logger = LogFactory.getLog(getClass()); | |
| private static final long serialVersionUID = 14535345L; | |
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| version: "2" | |
| services: | |
| zookeeper: | |
| image: confluentinc/cp-zookeeper:4.1.0 | |
| environment: | |
| ZOOKEEPER_CLIENT_PORT: 2181 | |
| ports: | |
| - 2181:2181 | |
| logging: |
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| [{"sap": { | |
| "latest": { | |
| "type": "INTERPRETER", | |
| "name": "sap", | |
| "version": "0.8.0", | |
| "published": "2018-06-24T01:29:37+00:00", | |
| "artifact": "sap@0.8.0", | |
| "description": "Zeppelin SAP support", | |
| "license": "Apache-2.0", | |
| "icon": "<i class=\"fa fa-rocket\"></i>", |
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| import org.apache.spark.ml.Pipeline | |
| import org.apache.spark.ml.evaluation.BinaryClassificationEvaluator | |
| import org.apache.spark.ml.feature.MinMaxScaler | |
| import org.apache.spark.ml.tuning.{CrossValidator, ParamGridBuilder} | |
| import org.apache.spark.sql.functions._ | |
| import org.apache.spark.sql.types.{IntegerType, LongType} | |
| import org.apache.spark.sql.SaveMode | |
| import org.apache.spark.ml.classification.LogisticRegression | |
| import org.apache.spark.ml.feature.VectorAssembler |
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