从 Spark 删除 Azure Cosmos DB for Apache Cassandra 表中的数据

Artículo
09/14/2024

适用对象： Cassandra

本文介绍了如何从 Spark 中删除 Azure Cosmos DB for Apache Cassandra 表中的数据。

API for Cassandra 配置

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

注意

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。

示例数据生成器

我们将使用此代码片段来生成示例数据：

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

//Create dataframe
val booksDF = Seq(
   ("b00001", "Arthur Conan Doyle", "A study in scarlet", 1887,11.33),
   ("b00023", "Arthur Conan Doyle", "A sign of four", 1890,22.45),
   ("b01001", "Arthur Conan Doyle", "The adventures of Sherlock Holmes", 1892,19.83),
   ("b00501", "Arthur Conan Doyle", "The memoirs of Sherlock Holmes", 1893,14.22),
   ("b00300", "Arthur Conan Doyle", "The hounds of Baskerville", 1901,12.25)
).toDF("book_id", "book_author", "book_name", "book_pub_year","book_price")

//Persist
booksDF.write
  .mode("append")
  .format("org.apache.spark.sql.cassandra")
  .options(Map( "table" -> "books", "keyspace" -> "books_ks", "output.consistency.level" -> "ALL", "ttl" -> "10000000"))
  .save()

数据帧 API

删除与条件匹配的行

//1) Create dataframe
val deleteBooksDF = spark
  .read
  .format("org.apache.spark.sql.cassandra")
  .options(Map( "table" -> "books", "keyspace" -> "books_ks"))
  .load
  .filter("book_id = 'b01001'")

//2) Review execution plan
deleteBooksDF.explain

//3) Review table data before execution
println("==================")
println("1) Before")
deleteBooksDF.show
println("==================")

//4) Delete selected records in dataframe
println("==================")
println("2a) Starting delete")

//Reuse connection for each partition
val cdbConnector = CassandraConnector(sc)
deleteBooksDF.foreachPartition((partition: Iterator[Row]) => {
  cdbConnector.withSessionDo(session =>
    partition.foreach{ book => 
        val delete = s"DELETE FROM books_ks.books where book_id='"+book.getString(0) +"';"
        session.execute(delete)
    })
})

println("2b) Completed delete")
println("==================")

//5) Review table data after delete operation
println("3) After")

spark
  .read
  .format("org.apache.spark.sql.cassandra")
  .options(Map( "table" -> "books", "keyspace" -> "books_ks"))
  .load
  .show

输出：

== Physical Plan ==
*(1) Filter (isnotnull(book_pub_year#486) && (book_pub_year#486 = 1887))
+- *(1) Scan org.apache.spark.sql.cassandra.CassandraSourceRelation@197cfae4 [book_id#482,book_author#483,book_name#484,book_price#485,book_pub_year#486] 
PushedFilters: [IsNotNull(book_pub_year), EqualTo(book_pub_year,1887)], 
ReadSchema: struct<book_id:string,book_author:sadamguan13
==================
1) Before
+-------+------------------+------------------+----------+-------------+
|book_id|       book_author|         book_name|book_price|book_pub_year|
+-------+------------------+------------------+----------+-------------+
| b00001|Arthur Conan Doyle|A study in scarlet|     11.33|         1887|
+-------+------------------+------------------+----------+-------------+

==================
==================
2a) Starting delete
2b) Completed delete
==================
3) After
+-------+------------------+--------------------+----------+-------------+
|book_id|       book_author|           book_name|book_price|book_pub_year|
+-------+------------------+--------------------+----------+-------------+
| b00300|Arthur Conan Doyle|The hounds of Bas...|     12.25|         1901|
| b03999|Arthur Conan Doyle|The adventure of ...|      null|         1892|
| b00023|Arthur Conan Doyle|      A sign of four|     22.45|         1890|
| b00501|Arthur Conan Doyle|The memoirs of Sh...|     14.22|         1893|
| b01001|Arthur Conan Doyle|The adventures of...|     19.83|         1892|
| b02999|Arthur Conan Doyle|  A case of identity|      15.0|         1891|
+-------+------------------+--------------------+----------+-------------+

deleteBooksDF: org.apache.spark.sql.Dataset[org.apache.spark.sql.Row] = [book_id: string, book_author: adamguan13
cdbConnector: com.datastax.spark.connector.cql.CassandraConnector = com.datastax.spark.connector.cql.CassandraConnector@187deb43

删除表中所有行

//1) Create dataframe
val deleteBooksDF = spark
  .read
  .format("org.apache.spark.sql.cassandra")
  .options(Map( "table" -> "books", "keyspace" -> "books_ks"))
  .load

//2) Review execution plan
deleteBooksDF.explain

//3) Review table data before execution
println("==================")
println("1) Before")
deleteBooksDF.show
println("==================")

//4) Delete selected records in dataframe
println("==================")
println("2a) Starting delete")

//Reuse connection for each partition
val cdbConnector = CassandraConnector(sc)
deleteBooksDF.foreachPartition((partition: Iterator[Row]) => {
  cdbConnector.withSessionDo(session =>
    partition.foreach{ book => 
        val delete = s"DELETE FROM books_ks.books where book_id='"+book.getString(0) +"';"
        session.execute(delete)
    })
})

println("2b) Completed delete")
println("==================")

//5) Review table data after delete operation
println("3) After")

spark
  .read
  .format("org.apache.spark.sql.cassandra")
  .options(Map( "table" -> "books", "keyspace" -> "books_ks"))
  .load
  .show

输出：

== Physical Plan ==
*(1) Scan org.apache.spark.sql.cassandra.CassandraSourceRelation@495377d7 [book_id#565,book_author#566,book_name#567,book_price#568,book_pub_year#569] 
PushedFilters: [], 
ReadSchema: struct<book_id:string,book_author:sadamguan13
==================
1) Before
+-------+------------------+--------------------+----------+-------------+
|book_id|       book_author|           book_name|book_price|book_pub_year|
+-------+------------------+--------------------+----------+-------------+
| b00300|Arthur Conan Doyle|The hounds of Bas...|     12.25|         1901|
| b03999|Arthur Conan Doyle|The adventure of ...|      null|         1892|
| b00023|Arthur Conan Doyle|      A sign of four|     22.45|         1890|
| b00501|Arthur Conan Doyle|The memoirs of Sh...|     14.22|         1893|
| b01001|Arthur Conan Doyle|The adventures of...|     19.83|         1892|
| b02999|Arthur Conan Doyle|  A case of identity|      15.0|         1891|
+-------+------------------+--------------------+----------+-------------+

==================
==================
2a) Starting delete
2b) Completed delete
==================
3) After
+-------+-----------+---------+----------+-------------+
|book_id|book_author|book_name|book_price|book_pub_year|
+-------+-----------+---------+----------+-------------+
+-------+-----------+---------+----------+-------------+

RDD API

删除表中所有行

//1) Create RDD with all rows
val deleteBooksRDD = 
    sc.cassandraTable("books_ks", "books")

//2) Review table data before execution
println("==================")
println("1) Before")
deleteBooksRDD.collect.foreach(println)
println("==================")

//3) Delete selected records in dataframe
println("==================")
println("2a) Starting delete")

/* Option 1: 
// Not supported currently
sc.cassandraTable("books_ks", "books")
  .where("book_pub_year = 1891")
  .deleteFromCassandra("books_ks", "books")
*/

//Option 2: CassandraConnector and CQL
//Reuse connection for each partition
val cdbConnector = CassandraConnector(sc)
deleteBooksRDD.foreachPartition(partition => {
    cdbConnector.withSessionDo(session =>
    partition.foreach{book => 
        val delete = s"DELETE FROM books_ks.books where book_id='"+ book.getString(0) +"';"
        session.execute(delete)
    }
   )
})

println("Completed delete")
println("==================")

println("2b) Completed delete")
println("==================")

//5) Review table data after delete operation
println("3) After")
sc.cassandraTable("books_ks", "books").collect.foreach(println)

输出：

==================
1) Before
CassandraRow{book_id: b00300, book_author: adamguan13
CassandraRow{book_id: b00001, book_author: adamguan13
CassandraRow{book_id: b00023, book_author: adamguan13
CassandraRow{book_id: b00501, book_author: adamguan13
CassandraRow{book_id: b01001, book_author: adamguan13
==================
==================
2a) Starting delete
Completed delete
==================
2b) Completed delete
==================
3) After
deleteBooksRDD: com.datastax.spark.connector.rdd.CassandraTableScanRDD[com.datastax.spark.connector.CassandraRow] = CassandraTableScanRDD[126] at RDD at CassandraRDD.scala:19
cdbConnector: com.datastax.spark.connector.cql.CassandraConnector = com.datastax.spark.connector.cql.CassandraConnector@317927

删除特定列

//1) Create RDD 
val deleteBooksRDD = 
    sc.cassandraTable("books_ks", "books")

//2) Review table data before execution
println("==================")
println("1) Before")
deleteBooksRDD.collect.foreach(println)
println("==================")

//3) Delete specific column values
println("==================")
println("2a) Starting delete of book price")

sc.cassandraTable("books_ks", "books")
  .deleteFromCassandra("books_ks", "books",SomeColumns("book_price"))

println("Completed delete")
println("==================")

println("2b) Completed delete")
println("==================")

//5) Review table data after delete operation
println("3) After")
sc.cassandraTable("books_ks", "books").take(4).foreach(println)

输出：

==================
1) Before
CassandraRow{book_id: b00300, book_author: adamguan13
CassandraRow{book_id: b00001, book_author: adamguan13
CassandraRow{book_id: b00023, book_author: adamguan13
CassandraRow{book_id: b00501, book_author: adamguan13
CassandraRow{book_id: b01001, book_author: adamguan13
==================
==================
2a) Starting delete of book price
Completed delete
==================
2b) Completed delete
==================
3) After
CassandraRow{book_id: b00300, book_author: adamguan13
CassandraRow{book_id: b00001, book_author: adamguan13
CassandraRow{book_id: b00023, book_author: adamguan13
CassandraRow{book_id: b00501, book_author: adamguan13
deleteBooksRDD: com.datastax.spark.connector.rdd.CassandraTableScanRDD[com.datastax.spark.connector.CassandraRow] = CassandraTableScanRDD[145] at RDD at CassandraRDD.scala:19

后续步骤

若要执行聚合和数据复制操作，请参阅 -

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从 Spark 删除 Azure Cosmos DB for Apache Cassandra 表中的数据

API for Cassandra 配置

示例数据生成器

数据帧 API

删除与条件匹配的行

删除表中所有行

RDD API

删除表中所有行

删除特定列

后续步骤

Recursos adicionales