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适用对象:
卡珊德拉
重要
你是否正在寻找一种数据库解决方案,以应对需要高扩展性、99.999% 可用性服务级别协议(SLA)、即时自动扩展和跨多个区域的自动故障转移的场景? 请考虑使用 Azure Cosmos DB for NoSQL。
本文介绍如何使用 Spark 将数据更新插入到支持 Apache Cassandra API 的 Azure Cosmos DB。
用于 Cassandra 配置的 API
在笔记本群集中设置以下 Spark 配置。 这是一次性活动。
//Connection-related
spark.cassandra.connection.host YOUR_ACCOUNT_NAME.cassandra.cosmosdb.azure.cn
spark.cassandra.connection.port 10350
spark.cassandra.connection.ssl.enabled true
spark.cassandra.auth.username YOUR_ACCOUNT_NAME
spark.cassandra.auth.password YOUR_ACCOUNT_KEY
// if using Spark 2.x
// spark.cassandra.connection.factory com.microsoft.azure.cosmosdb.cassandra.CosmosDbConnectionFactory
//Throughput-related...adjust as needed
spark.cassandra.output.batch.size.rows 1
// spark.cassandra.connection.connections_per_executor_max 10 // Spark 2.x
spark.cassandra.connection.remoteConnectionsPerExecutor 10 // Spark 3.x
spark.cassandra.output.concurrent.writes 1000
spark.cassandra.concurrent.reads 512
spark.cassandra.output.batch.grouping.buffer.size 1000
spark.cassandra.connection.keep_alive_ms 600000000
注释
如果使用的是 Spark 3.x,则无需安装 Azure Cosmos DB 帮助程序和连接工厂。 对于 Spark 3 连接器,还应该使用 remoteConnectionsPerExecutor 而不是 connections_per_executor_max(见上文)。
警告
本文展示的 Spark 3 示例已使用 Spark 3.2.1 版本和相应的 Cassandra Spark 连接器 com.datastax.spark:spark-cassandra-connector-assembly_2.12:3.2.0 测试过。 更高版本的 Spark 和/或 Cassandra 连接器可能无法按预期运行。
数据帧 API
创建数据框
import org.apache.spark.sql.cassandra._
//Spark connector
import com.datastax.spark.connector._
import com.datastax.spark.connector.cql.CassandraConnector
//if using Spark 2.x, CosmosDB library for multiple retry
//import com.microsoft.azure.cosmosdb.cassandra
// (1) Update: Changing author name to include prefix of "Sir"
// (2) Insert: adding a new book
val booksUpsertDF = Seq(
("b00001", "Sir Arthur Conan Doyle", "A study in scarlet", 1887),
("b00023", "Sir Arthur Conan Doyle", "A sign of four", 1890),
("b01001", "Sir Arthur Conan Doyle", "The adventures of Sherlock Holmes", 1892),
("b00501", "Sir Arthur Conan Doyle", "The memoirs of Sherlock Holmes", 1893),
("b00300", "Sir Arthur Conan Doyle", "The hounds of Baskerville", 1901),
("b09999", "Sir Arthur Conan Doyle", "The return of Sherlock Holmes", 1905)
).toDF("book_id", "book_author", "book_name", "book_pub_year")
booksUpsertDF.show()
插入或更新数据
// Upsert is no different from create
booksUpsertDF.write
.mode("append")
.format("org.apache.spark.sql.cassandra")
.options(Map( "table" -> "books", "keyspace" -> "books_ks"))
.save()
更新数据
//Cassandra connector instance
val cdbConnector = CassandraConnector(sc)
//This runs on the driver, leverage only for one off updates
cdbConnector.withSessionDo(session => session.execute("update books_ks.books set book_price=99.33 where book_id ='b00300' and book_pub_year = 1901;"))
RDD API
注释
在 RDD API 中的更新插入操作等同于创建操作
后续步骤
继续阅读下面的文章,对 Azure Cosmos DB for Apache Cassandra 表中存储的数据执行其他操作: