This topic describes how to use FeatureStore SDK for Java to read data such as offline features, real-time features, and sequence features from online data stores.
Prerequisites
A project, feature entities, feature views, and model features are created in FeatureStore. Data is synchronized between the online and offline data stores. For more information, see Configure a project in FeatureStore.
An AccessKey pair of your Alibaba Cloud account is obtained. For more information, see Create an AccessKey pair.
We recommend that you store your AccessKey ID and AccessKey secret in environment variables. For more information, see the Step 2: Configure environment variables section of the "Get started with Alibaba Cloud Darabonba SDK for Python topic.
Install FeatureStore SDK for Java
Download and install FeatureStore SDK for Java.
Initialize a FeatureStore client
API
Initialize the Configuration class.
Configuration configuration = new Configuration(regionId,accessKeyId,accessKeySecret,projectName);Parameters
Parameter | Example | Description |
regionId | cn-hangzhou | The ID of the region in which the FeatureStore client resides. |
accessKeyId | System.getenv("ACCESS_KEY_ID") | The AccessKey ID that is obtained from an environment variable. |
accessKeySecret | System.getenv("ACCESS_KEY_SECRET") | The AccessKey secret that is obtained from an environment variable. |
projectName | holo_pro | The name of the FeatureStore project. |
The FeatureStore client must run in a virtual private cloud (VPC) to allow FeatureStore SDK for Java to directly connect to the online data stores. For example, FeatureStore SDK for Java can access a Hologres instance or a GraphCompute instance only over a specific VPC.
Example
public class Constants {
public static String accessId = "";
public static String accessKey = "";
public static String host = "paifeaturestore.cn-hangzhou.aliyuncs.com";
static {
accessId = System.getenv("ACCESS_KEY_ID");// The System.getenv("") method is used to obtain the value of an environment variable.
accessKey = System.getenv("ACCESS_KEY_SECRET");
}
}// Initialize the Configuration class.
Configuration configuration = new Configuration("cn-hangzhou",Constants.accessId,
Constants.accessKey,"dec8");
configuration.setDomain(Constants.host);
ApiClient apiClient = new ApiClient(configuration);
FeatureStoreClient fsclient = new FeatureStoreClient(apiClient);Retrieve feature data from feature views
API
public FeatureResult getOnlineFeatures(String[] joinIds);// Query the full table without specifying aliases for specific fields.
public FeatureResult getOnlineFeatures(String[] joinIds, String[] features, Map<String, String> aliasFields);Parameters
Parameter | Example | Description |
joinIds | {"100001167","100001168"} | The array of values of the primary key field. Data is queried based on the specified values of the primary key field. |
features | {"user_id","city"} Note: You can use new String[]{"*"} to query all fields in the table. | The fields to be queried in the table. |
aliasFields | {"user_id":"uId"} | The aliases that are specified for fields in the table. The aliases are displayed in the data returned. |
Examples
Example 1: Retrieve feature data from an offline feature view
Obtain an offline feature view and retrieve feature data from the feature view
// get FeatureView By name //mo1(Offline FeatureView) FeatureView mo1 = project.getFeatureViewMap().get("mo1"); if(mo1==null){ throw new RuntimeException("This featureView is not exist"); } HashMap<String, String> ss = new HashMap<>(); FeatureResult features = mo1.getOnlineFeatures(new String[]{"100001167", "100004088","100006646"}, new String[]{"*"}, ss);Sample response
[ { "user_id":100001167, "gender":"male", "age":28, "city":"Shenyang" "item_cnt":0, "follow_cnt":0, "follower_cnt":0, "register_time":1696658585, "tags":"2", } { "user_id":100004088, "gender":"female", "age":28, "city":"Changchun" "item_cnt":0, "follow_cnt":8, "follower_cnt":0, "register_time":1695618449, "tags":"1", } { "user_id":100006646, "gender":"male", "age":28, "city":"Changchun" "item_cnt":0, "follow_cnt":1, "follower_cnt":1, "register_time":1698213339, "tags":"1", } ]
Example 2: Retrieve feature data from a real-time feature view
Obtain a real-time feature view and retrieve feature data from the feature view
// get FeatureView By name //tfv1(Online FeatureView) FeatureView tfv1 = project.getFeatureViewMap().get("tfv1"); if(tfv1==null){ throw new RuntimeException("This featureView is not exist"); } //Get data FeatureResult rf = tfv1.getOnlineFeatures(new String[]{"35d3d5a52a7515c2ca6bb4d8e965149b", "0ab7e3efacd56983f16503572d2b9915","84dfd3f91dd85ea105bc74a4f0d7a067"}, new String[]{"*"}, ss);Sample response
[ { "USER_MD5":"35d3d5a52a7515c2ca6bb4d8e965149b", "USER_NICKNAME":"Tom" } { "USER_MD5":"0ab7e3efacd56983f16503572d2b9915", "USER_NICKNAME":"Jack" } { "USER_MD5":"84dfd3f91dd85ea105bc74a4f0d7a067", "USER_NICKNAME":"Jerry" } ]
Example 3: Retrieve feature data from a sequence feature view
Obtain a sequence feature view and retrieve feature data from the feature view
// get FeatureView By name //ots_seq2(Sequence FeatureView) SequenceFeatureView ots_seq2 = project.getSeqFeatureView("ots_seq2"); if(ots_seq2==null){ throw new RuntimeException("This featureView is not exist"); } //get data FeatureResult features2 = ots_seq2.getOnlineFeatures(new String[]{"157843277", "157843278"});Sample response
[ { "click _50_seq_playtime":"null;15.0", "click_50_seq_event_time":"null;1704684504747", "click_50_seq_ts":"625662604;625662604", "user_id":"157843277", "click_50_seq":"null;200167895", "click_50_seq_event":"null;click", "click_50_seq_item_id":"null;200167895" } { "click_50_seq_playtime":"null;15.0", "click_50_seq_event_time":"null;1704684504747", "click_50_seq_ts":"625662604;625662604", "user_id":"157843278", "click_50_seq":"null;200167895", "click_50_seq_event":"null;click", "click_50_seq_item_id":"null;200167895" } ]
Retrieve feature data from model features
API
public FeatureResult getOnlineFeatures(Map<String, List<String>> joinIds);
public FeatureResult getOnlineFeaturesWithEntity(Map<String, List<String>> joinIds, String featureEntityName);Parameters
Parameter | Example | Description |
joinIds | [ "user_id": {"101598051", "101598471", "101601287" } ] | The map of join ID values. Each map element is a key-value pair of a specific join ID. The key is the name of the join ID, whereas the value is the value of the join ID. |
featureEntityName | "user" | The name of the feature entity for which you want to query feature data. |
Examples
Example 1: Retrieve feature data from a model feature, excluding sequence feature data
Each model feature can be associated with multiple feature entities. You can specify multiple join IDs to retrieve the corresponding features at a time.
In this example, the following
join IDsare specified:user_idanditem_id. For each join ID, the same number of values must be specified.//Obtain model features Model mf1 = project.getModelFeature("model_ots1"); HashMap<String, List<String>> mm = new HashMap<>(); mm.put("user_id", Arrays.asList("101598051", "101598471", "101601287")); mm.put("item_id",Arrays.asList("200004157", "200006185", "200034730"));Retrieve feature data from all the feature entities that are associated with a model feature
Retrieve feature data from all the feature entities that are associated with a model feature
//Get the data that all associated entities contain FeatureResult fr1 = mf1.getOnlineFeatures(mm);Sample response
[ { "user_id":101598051, "gender":"male", "age":28, "city":"Hangzhou", "item_cnt":0, "follow_cnt":0, "follower_cnt":0, "register_time":1695785665, "tags":"1", "item_id":200004157, "author":137649839, "category":2, "click_count":0, "duration":18.0, "praise_count":30, "pub_time":1698208690, "title":"#Workout Tracking" } { "user_id":200004157, "gender":"female", "age":31, "city":"Shenzhen" "item_cnt":0, "follow_cnt":1, "follower_cnt":0, "register_time":1695726582, "tags":"1", "item_id":200006185, "author":134195601, "category":14, "click_count":50, "duration":55.0, "praise_count":21, "pub_time":1696700908, "title":"#Idiom Story" } { "user_id":101601287, "gender":"female", "age":33, "city":"Shenzhen" "item_cnt":0, "follow_cnt":0, "follower_cnt":55, "register_time":1697519102, "tags":"0", "item_id":200034730, "author":112739045, "category":6, "click_count":2, "duration":9.0, "praise_count":0, "pub_time":1696568654, "title":"#Workout Tracking" } ]
Retrieve feature data of a specific feature entity that is associated with a model feature
Retrieve feature data of a specific feature entity that is associated with a model feature
// Retrieve only the feature data of the server feature entity. FeatureResult fr2 = mf1.getOnlineFeaturesWithEntity(mm, "server");Sample response
[ { "item_id":200004157, "author":137649839, "category":2, "click_count":0, "duration":18.0, "praise_count":30, "pub_time":1698208690, "title":"#Workout Tracking" }, { "item_id":200006185, "author":134195601, "category":14, "click_count":50, "duration":55.0, "praise_count":21, "pub_time":1696700908, "title":"#Idiom Story" }, { "item_id":200034730, "author":112739045, "category":6, "click_count":2, "duration":9.0, "praise_count":0, "pub_time":1696568654, "title":"#Workout Tracking" } ]
Example 2: Retrieve feature data from a model feature, including sequence feature data
Each model feature can be associated with multiple feature entities. You can specify multiple join IDs to retrieve the corresponding features at a time.
In this example, the following join ID is used:
user_id.// Retrieve feature data from a model feature, including sequence feature data. Model mdt1 =project.getModelFeature("mdt1"); if(mdt1==null){ throw new RuntimeException("This modelFeature is not exist"); } HashMap<String, List<String>> fsmap = new HashMap<>(); fsmap.put("user_id",Arrays.asList("100001167","100024146")); fsmap.put("item_id",Arrays.asList("200138790","200385417"));Retrieve feature data from all the feature entities that are associated with a model feature
Retrieve feature data from all the feature entities that are associated with a model feature
FeatureResult fr3 = mdt2.getOnlineFeatures(fsmap);Sample response
[ { "click_50_seq_event_time":"null;1698170945", "gender":"male", "click_50_seq_ts":"1704292557212;1704292557212", "city":"Shenyang", "item_id":"200138790", "click_50_seq":"null;204153583", "author":186784264, "pub_time":1696574947, "follower_cnt":0, "follow_cnt":0, "item_cnt":0, "click_count":2, "title":"#Idiom Story", "register_time":1696658585, "tags":2, "duration":13.0, "click_50_seq_playtime":"null;98.93932923011255", "user_id":"100001167", "praise_count":3, "click_50_seq_event":null;click, "category":20, "click_50_seq_item_id":null;204153583, "age":28, } { "click_50_seq_event_time":"null;1698180365", "gender":"male", "click_50_seq_ts":"1704292547792;1704292547792;1704292547792", "city":"Ningbo", "item_id":200385417, "click_50_seq":"null;299049390", "author":189247964, "pub_time":1696432224, "follower_cnt":47, "follow_cnt":0, "item_cnt":0, "click_count":4, "title":"#Idiom Story", "register_time":1697253820, "tags":1, "duration":"9.0", "click_50_seq_playtime":"null;32.15018252408633", "user_id":100024146, "praise_count":0, "click_50_seq_event":"null;click", "category":0, "click_50_seq_item_id":"null;299049390", "age":28, } { "click_50_seq_event_time":"null;1698170945", "gender":"male", "click_50_seq_ts":"1704292557212;1704292557212", "city":"Shenyang", "item_id":200138790, "click_50_seq":"null;204153583", "author":186784264, "pub_time":1696574947, "follower_cnt":0, "follow_cnt":0, "item_cnt":0, "click_count":2, "title":"#Idiom Story", "register_time":1696658585, "tags":2, "duration":13.0, "click_50_seq_playtime":"null;98.93932923011255", "user_id":"100001167", "praise_count":3, "click_50_seq_event":"null;click", "category":20, "click_50_seq_item_id":"null;204153583", "age":28, } { "click_50_seq_event_time":"null;1698180365", "gender":"male", "click_50_seq_ts":"1704292547792;1704292547792", "city":"Ningbo", "item_id":200385417, "click_50_seq":"null;299049390", "author":189247964, "pub_time":1696432224, "follower_cnt":47, "follow_cnt":0, "item_cnt":0, "click_count":4, "title":"#Idiom Story", "register_time":1697253820, "tags":1, "duration":9.0 "click_50_seq_playtime":"null;32.15018252408633", "user_id":"100024146", "praise_count":"0", "click_50_seq_event":"null;click", "category":0, "click_50_seq_item_id":"null;299049390", "age":28, } ]
Retrieve feature data of a specific feature entity that is associated with a model feature
Retrieve feature data of a specific feature entity that is associated with a model feature
FeatureResult fr4 = mdt1.getOnlineFeaturesWithEntity(fsmap, "client");Sample response
[ { "click_50_seq_event_time":"null;1698170945" "gender":"male" "click_50_seq_ts":"1704292555552;1704292555552" "city":"Shenyang" "click_50_seq":"null;204153583" "follower_cnt":0 "follow_cnt":0 "item_cnt":0 "register_time":1696658585 "tags":2 "click_50_seq_playtime":"null;98.93932923011255" "user_id":"100001167" "click_50_seq_event":"null;click" "click_50_seq_item_id":"null;204153583" "age":28 } { "click_50_seq_event_time":"null;1698180365", "gender":"male", "click_50_seq_ts":1704292546132;1704292546132;1704292546132, "city":"Ningbo", "click_50_seq":"null;299049390" "follower_cnt":47, "follow_cnt":0, "item_cnt":0, "register_time":1697253820, "tags":"1", "click_50_seq_playtime":"null;32.15018252408633", "user_id":100024146, "click_50_seq_event":"null;click", "click_50_seq_item_id":"null;299049390", "age":28 } { "click_50_seq_event_time":"null;1698170945", "gender":"male", "click_50_seq_ts":"1704292555552;1704292555552", "city":"Shenyang", "click_50_seq":"null;204153583", "follower_cnt":0, "follow_cnt":0, "item_cnt":0, "register_time":1696658585, "tags":2, "click_50_seq_playtime":"null;98.93932923011255", "user_id":"100001167", "click_50_seq_event":"null;click", "click_50_seq_item_id":"null;204153583", "age":28 } { "click_50_seq_event_time":"null;1698180365", "gender":"male", "click_50_seq_ts":"1704292546132;1704292546132;1704292546132", "city":"Ningbo", "click_50_seq":"null;299049390", "follower_cnt":47, "follow_cnt":0, "item_cnt":0, "register_time":1697253820, "tags":1, "click_50_seq_playtime":"null;32.15018252408633" "user_id":"100024146", "click_50_seq_event":"null;click", "click_50_seq_item_id":"null;299049390", "age":28 } ]