聊聊Spring AI的PgVectorStore-369IT编程

admin管理员组
文章数量:1031976

聊聊Spring AI的PgVectorStore

序

本文主要研究一下Spring AI的PgVectorStore

示例

pom.xml

代码语言：javascript代码运行次数：0运行复制

		<dependency>
			<groupId>org.springframework.ai</groupId>
			<artifactId>spring-ai-starter-vector-store-pgvector</artifactId>
		</dependency>

pgvector

代码语言：javascript代码运行次数：0运行复制

docker run -it --rm --name postgres -p 5432:5432 -e POSTGRES_USER=postgres -e POSTGRES_PASSWORD=postgres pgvector/pgvector:pg16

配置

代码语言：javascript代码运行次数：0运行复制

spring:
  datasource:
    name: pgvector
    driverClassName: org.postgresql.Driver
    url: jdbc:postgresql://localhost:5432/postgres?currentSchema=public&connectTimeout=60&socketTimeout=60
    username: postgres
    password: postgres
  ai:
    vectorstore:
      type: pgvector
      pgvector:
        initialize-schema: true
        index-type: HNSW
        distance-type: COSINE_DISTANCE
        dimensions: 1024
        max-document-batch-size: 10000
        schema-name: public
        table-name: vector_store

设置initialize-schema为true，默认会执行如下初始化脚本：

代码语言：javascript代码运行次数：0运行复制

CREATE EXTENSION IF NOT EXISTS vector;
CREATE EXTENSION IF NOT EXISTS hstore;
CREATE EXTENSION IF NOT EXISTS "uuid-ossp";

CREATE TABLE IF NOT EXISTS vector_store (
	id uuid DEFAULT uuid_generate_v4() PRIMARY KEY,
	content text,
	metadata json,
	embedding vector(1536) // 1536 is the default embedding dimension
);

CREATE INDEX ON vector_store USING HNSW (embedding vector_cosine_ops);

脚本源码： org/springframework/ai/vectorstore/pgvector/PgVectorStore.java

代码语言：javascript代码运行次数：0运行复制

	public void afterPropertiesSet() {

		logger.info("Initializing PGVectorStore schema for table: {} in schema: {}", this.getVectorTableName(),
				this.getSchemaName());

		logger.info("vectorTableValidationsEnabled {}", this.schemaValidation);

		if (this.schemaValidation) {
			this.schemaValidator.validateTableSchema(this.getSchemaName(), this.getVectorTableName());
		}

		if (!this.initializeSchema) {
			logger.debug("Skipping the schema initialization for the table: {}", this.getFullyQualifiedTableName());
			return;
		}

		// Enable the PGVector, JSONB and UUID support.
		this.jdbcTemplate.execute("CREATE EXTENSION IF NOT EXISTS vector");
		this.jdbcTemplate.execute("CREATE EXTENSION IF NOT EXISTS hstore");

		if (this.idType == PgIdType.UUID) {
			this.jdbcTemplate.execute("CREATE EXTENSION IF NOT EXISTS \"uuid-ossp\"");
		}

		this.jdbcTemplate.execute(String.format("CREATE SCHEMA IF NOT EXISTS %s", this.getSchemaName()));

		// Remove existing VectorStoreTable
		if (this.removeExistingVectorStoreTable) {
			this.jdbcTemplate.execute(String.format("DROP TABLE IF EXISTS %s", this.getFullyQualifiedTableName()));
		}

		this.jdbcTemplate.execute(String.format("""
				CREATE TABLE IF NOT EXISTS %s (
					id %s PRIMARY KEY,
					content text,
					metadata json,
					embedding vector(%d)
				)
				""", this.getFullyQualifiedTableName(), this.getColumnTypeName(), this.embeddingDimensions()));

		if (this.createIndexMethod != PgIndexType.NONE) {
			this.jdbcTemplate.execute(String.format("""
					CREATE INDEX IF NOT EXISTS %s ON %s USING %s (embedding %s)
					""", this.getVectorIndexName(), this.getFullyQualifiedTableName(), this.createIndexMethod,
					this.getDistanceType().index));
		}
	}

代码

代码语言：javascript代码运行次数：0运行复制

    @Test
    public void testAddAndSearch() {
        List<Document> documents = List.of(
                new Document("Spring AI rocks!! Spring AI rocks!! Spring AI rocks!! Spring AI rocks!! Spring AI rocks!!", Map.of("meta1", "meta1")),
                new Document("The World is Big and Salvation Lurks Around the Corner"),
                new Document("You walk forward facing the past and you turn back toward the future.", Map.of("meta2", "meta2")));

        // Add the documents to Milvus Vector Store
        pgVectorStore.add(documents);

        // Retrieve documents similar to a query
        List<Document> results = this.pgVectorStore.similaritySearch(SearchRequest.builder().query("Spring").topK(5).build());
        log.info("results:{}", JSON.toJSONString(results));
    }

输出如下：

代码语言：javascript代码运行次数：0运行复制

results:[{"contentFormatter":{"excludedEmbedMetadataKeys":[],"excludedInferenceMetadataKeys":[],"metadataSeparator":"\n","metadataTemplate":"{key}: {value}","textTemplate":"{metadata_string}\n\n{content}"},"formattedContent":"distance: 0.43509135\nmeta1: meta1\n\nSpring AI rocks!! Spring AI rocks!! Spring AI rocks!! Spring AI rocks!! Spring AI rocks!!","id":"9dbce9af-0451-4bdb-8f03-1f8b8c4d696f","metadata":{"distance":0.43509135,"meta1":"meta1"},"score":0.5649086534976959,"text":"Spring AI rocks!! Spring AI rocks!! Spring AI rocks!! Spring AI rocks!! Spring AI rocks!!"},{"contentFormatter":{"$ref":"$[0].contentFormatter"},"formattedContent":"distance: 0.57093126\n\nThe World is Big and Salvation Lurks Around the Corner","id":"92a45683-11fc-48b7-8676-dcca3b518dd4","metadata":{"distance":0.57093126},"score":0.42906874418258667,"text":"The World is Big and Salvation Lurks Around the Corner"},{"contentFormatter":{"$ref":"$[0].contentFormatter"},"formattedContent":"distance: 0.5936024\nmeta2: meta2\n\nYou walk forward facing the past and you turn back toward the future.","id":"298f6565-bcc7-4cbc-8552-4c0e2d021dbf","metadata":{"distance":0.5936024,"meta2":"meta2"},"score":0.40639758110046387,"text":"You walk forward facing the past and you turn back toward the future."}]

源码

PgVectorStoreAutoConfiguration

org/springframework/ai/vectorstore/pgvector/autoconfigure/PgVectorStoreAutoConfiguration.java

代码语言：javascript代码运行次数：0运行复制

@AutoConfiguration(after = JdbcTemplateAutoConfiguration.class)
@ConditionalOnClass({ PgVectorStore.class, DataSource.class, JdbcTemplate.class })
@EnableConfigurationProperties(PgVectorStoreProperties.class)
@ConditionalOnProperty(name = SpringAIVectorStoreTypes.TYPE, havingValue = SpringAIVectorStoreTypes.PGVECTOR,
		matchIfMissing = true)
public class PgVectorStoreAutoConfiguration {

	@Bean
	@ConditionalOnMissingBean(BatchingStrategy.class)
	BatchingStrategy pgVectorStoreBatchingStrategy() {
		return new TokenCountBatchingStrategy();
	}

	@Bean
	@ConditionalOnMissingBean
	public PgVectorStore vectorStore(JdbcTemplate jdbcTemplate, EmbeddingModel embeddingModel,
			PgVectorStoreProperties properties, ObjectProvider<ObservationRegistry> observationRegistry,
			ObjectProvider<VectorStoreObservationConvention> customObservationConvention,
			BatchingStrategy batchingStrategy) {

		var initializeSchema = properties.isInitializeSchema();

		return PgVectorStore.builder(jdbcTemplate, embeddingModel)
			.schemaName(properties.getSchemaName())
			.idType(properties.getIdType())
			.vectorTableName(properties.getTableName())
			.vectorTableValidationsEnabled(properties.isSchemaValidation())
			.dimensions(properties.getDimensions())
			.distanceType(properties.getDistanceType())
			.removeExistingVectorStoreTable(properties.isRemoveExistingVectorStoreTable())
			.indexType(properties.getIndexType())
			.initializeSchema(initializeSchema)
			.observationRegistry(observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP))
			.customObservationConvention(customObservationConvention.getIfAvailable(() -> null))
			.batchingStrategy(batchingStrategy)
			.maxDocumentBatchSize(properties.getMaxDocumentBatchSize())
			.build();
	}

}

PgVectorStoreAutoConfiguration在spring.ai.vectorstore.type为pgvector时会自动装配PgVectorStore，它依赖PgVectorStoreProperties及JdbcTemplateAutoConfiguration

PgVectorStoreProperties

org/springframework/ai/vectorstore/pgvector/autoconfigure/PgVectorStoreProperties.java

代码语言：javascript代码运行次数：0运行复制

@ConfigurationProperties(PgVectorStoreProperties.CONFIG_PREFIX)
public class PgVectorStoreProperties extends CommonVectorStoreProperties {

	public static final String CONFIG_PREFIX = "spring.ai.vectorstore.pgvector";

	private int dimensions = PgVectorStore.INVALID_EMBEDDING_DIMENSION;

	private PgIndexType indexType = PgIndexType.HNSW;

	private PgDistanceType distanceType = PgDistanceType.COSINE_DISTANCE;

	private boolean removeExistingVectorStoreTable = false;

	// Dynamically generate table name in PgVectorStore to allow backward compatibility
	private String tableName = PgVectorStore.DEFAULT_TABLE_NAME;

	private String schemaName = PgVectorStore.DEFAULT_SCHEMA_NAME;

	private PgVectorStore.PgIdType idType = PgVectorStore.PgIdType.UUID;

	private boolean schemaValidation = PgVectorStore.DEFAULT_SCHEMA_VALIDATION;

	private int maxDocumentBatchSize = PgVectorStore.MAX_DOCUMENT_BATCH_SIZE;

	//......
}

PgVectorStoreProperties继承了CommonVectorStoreProperties的initializeSchema配置，它提供了spring.ai.vectorstore.pgvector的配置，主要有dimensions、indexType、distanceType、removeExistingVectorStoreTable、tableName、schemaName、idType、schemaValidation、maxDocumentBatchSize这几个属性

JdbcTemplateAutoConfiguration

org/springframework/boot/autoconfigure/jdbc/JdbcTemplateAutoConfiguration.java

代码语言：javascript代码运行次数：0运行复制

@AutoConfiguration(after = DataSourceAutoConfiguration.class)
@ConditionalOnClass({ DataSource.class, JdbcTemplate.class })
@ConditionalOnSingleCandidate(DataSource.class)
@EnableConfigurationProperties(JdbcProperties.class)
@Import({ DatabaseInitializationDependencyConfigurer.class, JdbcTemplateConfiguration.class,
		NamedParameterJdbcTemplateConfiguration.class })
public class JdbcTemplateAutoConfiguration {

}

JdbcTemplateAutoConfiguration引入了DatabaseInitializationDependencyConfigurer、JdbcTemplateConfiguration、NamedParameterJdbcTemplateConfiguration

小结

Spring AI提供了spring-ai-starter-vector-store-pgvector用于自动装配PgVectorStore。除了spring.ai.vectorstore.pgvector的配置，还需要配置spring.datasource。

doc

vectordbs/pgvector

聊聊Spring AI的PgVectorStore

序

本文主要研究一下Spring AI的PgVectorStore

示例

pom.xml

代码语言：javascript代码运行次数：0运行复制

		<dependency>
			<groupId>org.springframework.ai</groupId>
			<artifactId>spring-ai-starter-vector-store-pgvector</artifactId>
		</dependency>

pgvector

代码语言：javascript代码运行次数：0运行复制

docker run -it --rm --name postgres -p 5432:5432 -e POSTGRES_USER=postgres -e POSTGRES_PASSWORD=postgres pgvector/pgvector:pg16

配置

代码语言：javascript代码运行次数：0运行复制

spring:
  datasource:
    name: pgvector
    driverClassName: org.postgresql.Driver
    url: jdbc:postgresql://localhost:5432/postgres?currentSchema=public&connectTimeout=60&socketTimeout=60
    username: postgres
    password: postgres
  ai:
    vectorstore:
      type: pgvector
      pgvector:
        initialize-schema: true
        index-type: HNSW
        distance-type: COSINE_DISTANCE
        dimensions: 1024
        max-document-batch-size: 10000
        schema-name: public
        table-name: vector_store

设置initialize-schema为true，默认会执行如下初始化脚本：

代码语言：javascript代码运行次数：0运行复制

CREATE EXTENSION IF NOT EXISTS vector;
CREATE EXTENSION IF NOT EXISTS hstore;
CREATE EXTENSION IF NOT EXISTS "uuid-ossp";

CREATE TABLE IF NOT EXISTS vector_store (
	id uuid DEFAULT uuid_generate_v4() PRIMARY KEY,
	content text,
	metadata json,
	embedding vector(1536) // 1536 is the default embedding dimension
);

CREATE INDEX ON vector_store USING HNSW (embedding vector_cosine_ops);

脚本源码： org/springframework/ai/vectorstore/pgvector/PgVectorStore.java

代码语言：javascript代码运行次数：0运行复制

	public void afterPropertiesSet() {

		logger.info("Initializing PGVectorStore schema for table: {} in schema: {}", this.getVectorTableName(),
				this.getSchemaName());

		logger.info("vectorTableValidationsEnabled {}", this.schemaValidation);

		if (this.schemaValidation) {
			this.schemaValidator.validateTableSchema(this.getSchemaName(), this.getVectorTableName());
		}

		if (!this.initializeSchema) {
			logger.debug("Skipping the schema initialization for the table: {}", this.getFullyQualifiedTableName());
			return;
		}

		// Enable the PGVector, JSONB and UUID support.
		this.jdbcTemplate.execute("CREATE EXTENSION IF NOT EXISTS vector");
		this.jdbcTemplate.execute("CREATE EXTENSION IF NOT EXISTS hstore");

		if (this.idType == PgIdType.UUID) {
			this.jdbcTemplate.execute("CREATE EXTENSION IF NOT EXISTS \"uuid-ossp\"");
		}

		this.jdbcTemplate.execute(String.format("CREATE SCHEMA IF NOT EXISTS %s", this.getSchemaName()));

		// Remove existing VectorStoreTable
		if (this.removeExistingVectorStoreTable) {
			this.jdbcTemplate.execute(String.format("DROP TABLE IF EXISTS %s", this.getFullyQualifiedTableName()));
		}

		this.jdbcTemplate.execute(String.format("""
				CREATE TABLE IF NOT EXISTS %s (
					id %s PRIMARY KEY,
					content text,
					metadata json,
					embedding vector(%d)
				)
				""", this.getFullyQualifiedTableName(), this.getColumnTypeName(), this.embeddingDimensions()));

		if (this.createIndexMethod != PgIndexType.NONE) {
			this.jdbcTemplate.execute(String.format("""
					CREATE INDEX IF NOT EXISTS %s ON %s USING %s (embedding %s)
					""", this.getVectorIndexName(), this.getFullyQualifiedTableName(), this.createIndexMethod,
					this.getDistanceType().index));
		}
	}

代码

代码语言：javascript代码运行次数：0运行复制

    @Test
    public void testAddAndSearch() {
        List<Document> documents = List.of(
                new Document("Spring AI rocks!! Spring AI rocks!! Spring AI rocks!! Spring AI rocks!! Spring AI rocks!!", Map.of("meta1", "meta1")),
                new Document("The World is Big and Salvation Lurks Around the Corner"),
                new Document("You walk forward facing the past and you turn back toward the future.", Map.of("meta2", "meta2")));

        // Add the documents to Milvus Vector Store
        pgVectorStore.add(documents);

        // Retrieve documents similar to a query
        List<Document> results = this.pgVectorStore.similaritySearch(SearchRequest.builder().query("Spring").topK(5).build());
        log.info("results:{}", JSON.toJSONString(results));
    }

输出如下：

代码语言：javascript代码运行次数：0运行复制

results:[{"contentFormatter":{"excludedEmbedMetadataKeys":[],"excludedInferenceMetadataKeys":[],"metadataSeparator":"\n","metadataTemplate":"{key}: {value}","textTemplate":"{metadata_string}\n\n{content}"},"formattedContent":"distance: 0.43509135\nmeta1: meta1\n\nSpring AI rocks!! Spring AI rocks!! Spring AI rocks!! Spring AI rocks!! Spring AI rocks!!","id":"9dbce9af-0451-4bdb-8f03-1f8b8c4d696f","metadata":{"distance":0.43509135,"meta1":"meta1"},"score":0.5649086534976959,"text":"Spring AI rocks!! Spring AI rocks!! Spring AI rocks!! Spring AI rocks!! Spring AI rocks!!"},{"contentFormatter":{"$ref":"$[0].contentFormatter"},"formattedContent":"distance: 0.57093126\n\nThe World is Big and Salvation Lurks Around the Corner","id":"92a45683-11fc-48b7-8676-dcca3b518dd4","metadata":{"distance":0.57093126},"score":0.42906874418258667,"text":"The World is Big and Salvation Lurks Around the Corner"},{"contentFormatter":{"$ref":"$[0].contentFormatter"},"formattedContent":"distance: 0.5936024\nmeta2: meta2\n\nYou walk forward facing the past and you turn back toward the future.","id":"298f6565-bcc7-4cbc-8552-4c0e2d021dbf","metadata":{"distance":0.5936024,"meta2":"meta2"},"score":0.40639758110046387,"text":"You walk forward facing the past and you turn back toward the future."}]

源码

PgVectorStoreAutoConfiguration

org/springframework/ai/vectorstore/pgvector/autoconfigure/PgVectorStoreAutoConfiguration.java

代码语言：javascript代码运行次数：0运行复制

@AutoConfiguration(after = JdbcTemplateAutoConfiguration.class)
@ConditionalOnClass({ PgVectorStore.class, DataSource.class, JdbcTemplate.class })
@EnableConfigurationProperties(PgVectorStoreProperties.class)
@ConditionalOnProperty(name = SpringAIVectorStoreTypes.TYPE, havingValue = SpringAIVectorStoreTypes.PGVECTOR,
		matchIfMissing = true)
public class PgVectorStoreAutoConfiguration {

	@Bean
	@ConditionalOnMissingBean(BatchingStrategy.class)
	BatchingStrategy pgVectorStoreBatchingStrategy() {
		return new TokenCountBatchingStrategy();
	}

	@Bean
	@ConditionalOnMissingBean
	public PgVectorStore vectorStore(JdbcTemplate jdbcTemplate, EmbeddingModel embeddingModel,
			PgVectorStoreProperties properties, ObjectProvider<ObservationRegistry> observationRegistry,
			ObjectProvider<VectorStoreObservationConvention> customObservationConvention,
			BatchingStrategy batchingStrategy) {

		var initializeSchema = properties.isInitializeSchema();

		return PgVectorStore.builder(jdbcTemplate, embeddingModel)
			.schemaName(properties.getSchemaName())
			.idType(properties.getIdType())
			.vectorTableName(properties.getTableName())
			.vectorTableValidationsEnabled(properties.isSchemaValidation())
			.dimensions(properties.getDimensions())
			.distanceType(properties.getDistanceType())
			.removeExistingVectorStoreTable(properties.isRemoveExistingVectorStoreTable())
			.indexType(properties.getIndexType())
			.initializeSchema(initializeSchema)
			.observationRegistry(observationRegistry.getIfUnique(() -> ObservationRegistry.NOOP))
			.customObservationConvention(customObservationConvention.getIfAvailable(() -> null))
			.batchingStrategy(batchingStrategy)
			.maxDocumentBatchSize(properties.getMaxDocumentBatchSize())
			.build();
	}

}

PgVectorStoreAutoConfiguration在spring.ai.vectorstore.type为pgvector时会自动装配PgVectorStore，它依赖PgVectorStoreProperties及JdbcTemplateAutoConfiguration

PgVectorStoreProperties

org/springframework/ai/vectorstore/pgvector/autoconfigure/PgVectorStoreProperties.java

代码语言：javascript代码运行次数：0运行复制

@ConfigurationProperties(PgVectorStoreProperties.CONFIG_PREFIX)
public class PgVectorStoreProperties extends CommonVectorStoreProperties {

	public static final String CONFIG_PREFIX = "spring.ai.vectorstore.pgvector";

	private int dimensions = PgVectorStore.INVALID_EMBEDDING_DIMENSION;

	private PgIndexType indexType = PgIndexType.HNSW;

	private PgDistanceType distanceType = PgDistanceType.COSINE_DISTANCE;

	private boolean removeExistingVectorStoreTable = false;

	// Dynamically generate table name in PgVectorStore to allow backward compatibility
	private String tableName = PgVectorStore.DEFAULT_TABLE_NAME;

	private String schemaName = PgVectorStore.DEFAULT_SCHEMA_NAME;

	private PgVectorStore.PgIdType idType = PgVectorStore.PgIdType.UUID;

	private boolean schemaValidation = PgVectorStore.DEFAULT_SCHEMA_VALIDATION;

	private int maxDocumentBatchSize = PgVectorStore.MAX_DOCUMENT_BATCH_SIZE;

	//......
}

PgVectorStoreProperties继承了CommonVectorStoreProperties的initializeSchema配置，它提供了spring.ai.vectorstore.pgvector的配置，主要有dimensions、indexType、distanceType、removeExistingVectorStoreTable、tableName、schemaName、idType、schemaValidation、maxDocumentBatchSize这几个属性

JdbcTemplateAutoConfiguration

org/springframework/boot/autoconfigure/jdbc/JdbcTemplateAutoConfiguration.java

代码语言：javascript代码运行次数：0运行复制

@AutoConfiguration(after = DataSourceAutoConfiguration.class)
@ConditionalOnClass({ DataSource.class, JdbcTemplate.class })
@ConditionalOnSingleCandidate(DataSource.class)
@EnableConfigurationProperties(JdbcProperties.class)
@Import({ DatabaseInitializationDependencyConfigurer.class, JdbcTemplateConfiguration.class,
		NamedParameterJdbcTemplateConfiguration.class })
public class JdbcTemplateAutoConfiguration {

}

JdbcTemplateAutoConfiguration引入了DatabaseInitializationDependencyConfigurer、JdbcTemplateConfiguration、NamedParameterJdbcTemplateConfiguration

小结

Spring AI提供了spring-ai-starter-vector-store-pgvector用于自动装配PgVectorStore。除了spring.ai.vectorstore.pgvector的配置，还需要配置spring.datasource。

doc

vectordbs/pgvector

本文标签：聊聊Spring AI的PgVectorStore

版权声明：本文标题：聊聊Spring AI的PgVectorStore 内容由热心网友自发贡献，该文观点仅代表作者本人，转载请联系作者并注明出处：http://it.en369.cn/jiaocheng/1747873809a2220918.html，本站仅提供信息存储空间服务，不拥有所有权，不承担相关法律责任。如发现本站有涉嫌抄袭侵权/违法违规的内容，一经查实，本站将立刻删除。

369IT编程

聊聊Spring AI的PgVectorStore

聊聊Spring AI的PgVectorStore

序

示例

pom.xml

pgvector

配置

代码

源码

PgVectorStoreAutoConfiguration

PgVectorStoreProperties

JdbcTemplateAutoConfiguration

小结

doc

聊聊Spring AI的PgVectorStore

序

示例

pom.xml

pgvector

配置

代码

源码

PgVectorStoreAutoConfiguration

PgVectorStoreProperties

JdbcTemplateAutoConfiguration

小结

doc

更多相关文章

聊聊Spring AI的PgVectorStore

发表评论

推荐文章

Windows照片查看器无法显示此图片，因为计算机上的可用内存可能不足的最好解决办法。

tRPC智能体生态又升级：发布A2A协议的实现trpc

从0到1：让AI赋能计算机的全流程实践指南

区块链 RWA系统的主要功能

2023年最新java面试题及答案

热门文章

被问了很多次的富集分析绘图教程，0基础也能1分钟完成

C++23中的std::forward

延迟、丢包和抖动——故障测试必知必会

【关注可白嫖源码】-SSM公司会议管理系统

Mono for Android——使用C#，在手机上运行

如何手搓一个便携式显示器

Power BI 表格添加视频

AI席卷校园：百万条对话揭秘，Claude是代码救星还是作弊工具？

centos命令行安装MySQL(云原生POD命令行安装MySQL)

一文读懂开源 Llama 4 模型

最新文章

常用开源工作流引擎Activiti JBPM Flowable Bonita Airflow

java.util.concurrent 概述

最新最全的Activiti开源工作流引擎面试题

Java中的信号量semaphore

开源工作流引擎Flowable的面试题

程序员刚毕业，先去大厂镀金还是先去小厂攒经验？

万象2008清空boss账户密码

【Tools】GitBook简明教程

oracle exadata celldisk 闪存盘受损导致性能下降

SDUT 2138 图结构练习——BFSDFS——判断可达性

javascript - Type &#39;undefined&#39; is not assignable to type &#39;menuItemProps[]&#39; - Stack Overflow

javascript - VS 2015 Angular 2 import modules cannot be resolved - Stack Overflow

javascript - Get the JSON objects that are not present in another array - Stack Overflow

javascript - How to dismiss a phonegap notification programmatically - Stack Overflow

c - Solaris 10 make Error code 1 Fatal Error when trying to build python 2.7.16 - Stack Overflow

javascript - Type 'undefined' is not assignable to type 'menuItemProps[]' - Stack Overflow