這是一個Demo，大家可以一起學習，一起交流，有問題的可以私信，或者留言

本文使用 Azure Databricks 執(zhí)行 ETL（提取、轉換和加載數據）操作。?將數據從 Azure Data Lake Storage Gen2 提取到 Azure Databricks 中，在 Azure Databricks 中對數據運行轉換操作，然后將轉換的數據加載到 Azure Synapse Analytics 中。

本文的步驟使用 Azure Databricks 的 Azure Synapse 連接器將數據傳輸到 Azure Databricks。?而此連接器又使用 Azure Blob 存儲來臨時存儲在 Azure Databricks 群集和 Azure Synapse 之間傳輸的數據。

下圖演示了應用程序流：

?

創(chuàng)建 Azure Databricks 服務

在本部分中，你將使用 Azure 門戶創(chuàng)建 Azure Databricks 服務。

在 Azure 菜單中，選擇“創(chuàng)建資源” 。

然后，選擇“分析” > “Azure Databricks” 。

在“Azure Databricks 服務” 下，提供以下值來創(chuàng)建 Databricks 服務：

表 1properties說明

工作區(qū)名稱	為 Databricks 工作區(qū)提供一個名稱。
訂閱	從下拉列表中選擇自己的 Azure 訂閱。
資源組	指定是要創(chuàng)建新的資源組還是使用現(xiàn)有的資源組。?資源組是用于保存 Azure 解決方案相關資源的容器。?有關詳細信息，請參閱?Azure 資源組概述。
位置	選擇“China East 2 ”。?有關其他可用區(qū)域，請參閱各區(qū)域推出的 Azure 服務。
定價層	選擇“標準” 。

創(chuàng)建帳戶需要幾分鐘時間。?若要監(jiān)視操作狀態(tài)，請查看頂部的進度欄。

選擇“固定到儀表板” ，然后選擇“創(chuàng)建” 。

在 Azure Databricks 中創(chuàng)建 Spark 群集

在 Azure 門戶中，轉到所創(chuàng)建的 Databricks 服務，然后選擇“啟動工作區(qū)”。

系統(tǒng)隨后會將你重定向到 Azure Databricks 門戶。?在門戶中選擇“群集”。

在“新建群集”頁中，提供用于創(chuàng)建群集的值。

填寫以下字段的值，對于其他字段接受默認值：

• 輸入群集的名稱。

• 請務必選中“在不活動超過 __ 分鐘后終止” 復選框。?如果未使用群集，則請?zhí)峁┮粋€持續(xù)時間（以分鐘為單位），超過該時間后群集會被終止。

• 選擇“創(chuàng)建群集”。?群集運行后，可將筆記本附加到該群集，并運行 Spark 作業(yè)。

在 Azure Data Lake Storage Gen2 帳戶中創(chuàng)建文件系統(tǒng)

在本部分中，你將在 Azure Databricks 工作區(qū)中創(chuàng)建一個 Notebook，然后運行代碼片段來配置存儲帳戶

在?Azure 門戶中，轉到你創(chuàng)建的 Azure Databricks 服務，然后選擇“啟動工作區(qū)”。

在左側選擇“工作區(qū)” 。?在?工作區(qū)?下拉列表中，選擇?創(chuàng)建?>?筆記本?。

在“創(chuàng)建 Notebook”對話框中，輸入 Notebook 的名稱。?選擇“Scala”作為語言，然后選擇前面創(chuàng)建的 Spark 群集。

選擇“創(chuàng)建” 。

以下代碼塊設置 Spark 會話中訪問的任何 ADLS Gen 2 帳戶的默認服務主體憑據。?第二個代碼塊會將帳戶名稱追加到該設置，從而指定特定的 ADLS Gen 2 帳戶的憑據。?將任一代碼塊復制并粘貼到 Azure Databricks 筆記本的第一個單元格中。

會話配置

Scala復制

val appID = "<appID>" val secret = "<secret>" val tenantID = "<tenant-id>"spark.conf.set("fs.azure.account.auth.type", "OAuth") spark.conf.set("fs.azure.account.oauth.provider.type", "org.apache.hadoop.fs.azurebfs.oauth2.ClientCredsTokenProvider") spark.conf.set("fs.azure.account.oauth2.client.id", "<appID>") spark.conf.set("fs.azure.account.oauth2.client.secret", "<secret>") spark.conf.set("fs.azure.account.oauth2.client.endpoint", "https://login.microsoftonline.com/<tenant-id>/oauth2/token") spark.conf.set("fs.azure.createRemoteFileSystemDuringInitialization", "true")

帳戶配置

Scala復制

val storageAccountName = "<storage-account-name>" val appID = "<app-id>" val secret = "<secret>" val fileSystemName = "<file-system-name>" val tenantID = "<tenant-id>"spark.conf.set("fs.azure.account.auth.type." + storageAccountName + ".dfs.core.chinacloudapi.cn", "OAuth") spark.conf.set("fs.azure.account.oauth.provider.type." + storageAccountName + ".dfs.core.chinacloudapi.cn", "org.apache.hadoop.fs.azurebfs.oauth2.ClientCredsTokenProvider") spark.conf.set("fs.azure.account.oauth2.client.id." + storageAccountName + ".dfs.core.chinacloudapi.cn", "" + appID + "") spark.conf.set("fs.azure.account.oauth2.client.secret." + storageAccountName + ".dfs.core.chinacloudapi.cn", "" + secret + "") spark.conf.set("fs.azure.account.oauth2.client.endpoint." + storageAccountName + ".dfs.core.chinacloudapi.cn", "https://login.microsoftonline.com/" + tenantID + "/oauth2/token") spark.conf.set("fs.azure.createRemoteFileSystemDuringInitialization", "true") dbutils.fs.ls("abfss://" + fileSystemName + "@" + storageAccountName + ".dfs.core.chinacloudapi.cn/") spark.conf.set("fs.azure.createRemoteFileSystemDuringInitialization", "false")

在此代碼塊中，請將?<app-id>、<secret>、<tenant-id>?和?<storage-account-name>?占位符值替換為在完成本教程的先決條件時收集的值。?將?<file-system-name>?占位符值替換為你想要為文件系統(tǒng)指定的任何名稱。

• <app-id>?和?<secret>?來自在創(chuàng)建服務主體的過程中向 active directory 注冊的應用。

• <tenant-id>?來自你的訂閱。

• <storage-account-name>?是 Azure Data Lake Storage Gen2 存儲帳戶的名稱。

按?SHIFT + ENTER?鍵，運行此塊中的代碼。

注意：這些參數要看你使用的Azure是國際版還是中國版，本文使用的是中國版，如是國際版則需要將dfs.core.chinacloudapi.cn改成國際版的

將示例數據引入 Azure Data Lake Storage Gen2 帳戶

將以下代碼輸入到 Notebook 單元格中：

復制

%sh wget -P /tmp https://raw.githubusercontent.com/Azure/usql/master/Examples/Samples/Data/json/radiowebsite/small_radio_json.json

下面是small_radio_json.json的內容，如果上面的執(zhí)行不成功的話，可以復制，粘貼，上傳到到Azure Data Lake Storage Gen2 上

{"ts":1409318650332,"userId":"309","sessionId":1879,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"free","itemInSession":2,"location":"Killeen-Temple, TX","lastName":"Montgomery","firstName":"Annalyse","registration":1384448062332,"gender":"F","artist":"El Arrebato","song":"Quiero Quererte Querer","length":234.57914} {"ts":1409318653332,"userId":"11","sessionId":10,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"paid","itemInSession":9,"location":"Anchorage, AK","lastName":"Thomas","firstName":"Dylann","registration":1400723739332,"gender":"M","artist":"Creedence Clearwater Revival","song":"Born To Move","length":340.87138} {"ts":1409318685332,"userId":"201","sessionId":2047,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"paid","itemInSession":11,"location":"New York-Newark-Jersey City, NY-NJ-PA","lastName":"Watts","firstName":"Liam","registration":1406279422332,"gender":"M","artist":"Gorillaz","song":"DARE","length":246.17751} {"ts":1409318686332,"userId":"779","sessionId":2136,"page":"Home","auth":"Logged In","method":"GET","status":200,"level":"free","itemInSession":0,"location":"Nashville-Davidson--Murfreesboro--Franklin, TN","lastName":"Townsend","firstName":"Tess","registration":1406970190332,"gender":"F"} {"ts":1409318697332,"userId":"401","sessionId":400,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"free","itemInSession":2,"location":"Atlanta-Sandy Springs-Roswell, GA","lastName":"Smith","firstName":"Margaux","registration":1406191211332,"gender":"F","artist":"Otis Redding","song":"Send Me Some Lovin'","length":135.57506} {"ts":1409318714332,"userId":"521","sessionId":520,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"paid","itemInSession":39,"location":"Chicago-Naperville-Elgin, IL-IN-WI","lastName":"Morse","firstName":"Alan","registration":1401760632332,"gender":"M","artist":"Slightly Stoopid","song":"Mellow Mood","length":198.53016} {"ts":1409318743332,"userId":"244","sessionId":2261,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"free","itemInSession":1,"location":"San Jose-Sunnyvale-Santa Clara, CA","lastName":"Shelton","firstName":"Gabriella","registration":1389460542332,"gender":"F","artist":"NOFX","song":"Linoleum","length":130.2722} {"ts":1409318804332,"userId":"969","sessionId":968,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"paid","itemInSession":0,"location":"Detroit-Warren-Dearborn, MI","lastName":"Williams","firstName":"Elijah","registration":1388691347332,"gender":"M","artist":"Nirvana","song":"The Man Who Sold The World","length":260.98893} {"ts":1409318832332,"userId":"401","sessionId":400,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"free","itemInSession":3,"location":"Atlanta-Sandy Springs-Roswell, GA","lastName":"Smith","firstName":"Margaux","registration":1406191211332,"gender":"F","artist":"Aventura","song":"La Nina","length":293.56363} {"ts":1409318891332,"userId":"779","sessionId":2136,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"free","itemInSession":1,"location":"Nashville-Davidson--Murfreesboro--Franklin, TN","lastName":"Townsend","firstName":"Tess","registration":1406970190332,"gender":"F","artist":"Harmonia","song":"Sehr kosmisch","length":655.77751} {"ts":1409318912332,"userId":"521","sessionId":520,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"paid","itemInSession":40,"location":"Chicago-Naperville-Elgin, IL-IN-WI","lastName":"Morse","firstName":"Alan","registration":1401760632332,"gender":"M","artist":"Spragga Benz","song":"Backshot","length":122.53995} {"ts":1409318931332,"userId":"201","sessionId":2047,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"paid","itemInSession":12,"location":"New York-Newark-Jersey City, NY-NJ-PA","lastName":"Watts","firstName":"Liam","registration":1406279422332,"gender":"M","artist":"Bananarama","song":"Love In The First Degree","length":208.92689} {"ts":1409318931332,"userId":"201","sessionId":2047,"page":"Home","auth":"Logged In","method":"GET","status":200,"level":"paid","itemInSession":13,"location":"New York-Newark-Jersey City, NY-NJ-PA","lastName":"Watts","firstName":"Liam","registration":1406279422332,"gender":"M"} {"ts":1409318993332,"userId":"11","sessionId":10,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"paid","itemInSession":10,"location":"Anchorage, AK","lastName":"Thomas","firstName":"Dylann","registration":1400723739332,"gender":"M","artist":"Alliance Ethnik","song":"Repr???sente","length":252.21179} {"ts":1409319034332,"userId":"521","sessionId":520,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"paid","itemInSession":41,"location":"Chicago-Naperville-Elgin, IL-IN-WI","lastName":"Morse","firstName":"Alan","registration":1401760632332,"gender":"M","artist":"Sense Field","song":"Am I A Fool","length":181.86404} {"ts":1409319064332,"userId":"969","sessionId":968,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"paid","itemInSession":1,"location":"Detroit-Warren-Dearborn, MI","lastName":"Williams","firstName":"Elijah","registration":1388691347332,"gender":"M","artist":"Binary Star","song":"Solar Powered","length":268.93016} {"ts":1409319125332,"userId":"401","sessionId":400,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"free","itemInSession":4,"location":"Atlanta-Sandy Springs-Roswell, GA","lastName":"Smith","firstName":"Margaux","registration":1406191211332,"gender":"F","artist":"Sarah Borges and the Broken Singles","song":"Do It For Free","length":158.95465} {"ts":1409319215332,"userId":"521","sessionId":520,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"paid","itemInSession":42,"location":"Chicago-Naperville-Elgin, IL-IN-WI","lastName":"Morse","firstName":"Alan","registration":1401760632332,"gender":"M","artist":"Incubus","song":"Drive","length":232.46322} {"ts":1409319245332,"userId":"11","sessionId":10,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"paid","itemInSession":11,"location":"Anchorage, AK","lastName":"Thomas","firstName":"Dylann","registration":1400723739332,"gender":"M","artist":"Ella Fitzgerald","song":"On Green Dolphin Street (Medley) (1999 Digital Remaster)","length":427.15383} {"ts":1409319283332,"userId":"401","sessionId":400,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"free","itemInSession":5,"location":"Atlanta-Sandy Springs-Roswell, GA","lastName":"Smith","firstName":"Margaux","registration":1406191211332,"gender":"F","artist":"10cc","song":"Silly Love","length":241.34485} {"ts":1409319293332,"userId":"906","sessionId":1909,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"free","itemInSession":0,"location":"Toledo, OH","lastName":"Oconnell","firstName":"Aurora","registration":1406406461332,"gender":"F","artist":"Eric Johnson","song":"Trail Of Tears (Album Version)","length":361.37751} {"ts":1409319332332,"userId":"969","sessionId":968,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"paid","itemInSession":2,"location":"Detroit-Warren-Dearborn, MI","lastName":"Williams","firstName":"Elijah","registration":1388691347332,"gender":"M","artist":"Phoenix","song":"Holdin' On Together","length":207.15057} {"ts":1409319365332,"userId":"750","sessionId":749,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"free","itemInSession":0,"location":"Grants Pass, OR","lastName":"Coleman","firstName":"Alex","registration":1404326435332,"gender":"M","artist":"Ween","song":"The Stallion","length":276.13995} {"ts":1409319447332,"userId":"521","sessionId":520,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"paid","itemInSession":43,"location":"Chicago-Naperville-Elgin, IL-IN-WI","lastName":"Morse","firstName":"Alan","registration":1401760632332,"gender":"M","artist":"dEUS","song":"Secret Hell","length":299.83302} {"ts":1409319539332,"userId":"969","sessionId":968,"page":"NextSong","auth":"Logged In","method":"PUT","status":200,"level":"paid","itemInSession":3,"location":"Detroit-Warren-Dearborn, MI","lastName":"Williams","firstName":"Elijah","registration":1388691347332,"gender":"M","artist":"Holly Cole","song":"Cry (If You Want To)","length":158.98077}

?

從 Azure Data Lake Storage Gen2 帳戶中提取數據

現(xiàn)在可以將示例 json 文件加載為 Azure Databricks 中的數據幀。?將以下代碼粘貼到新單元格中。?將括號中顯示的占位符替換為你的值。

Scala復制

val df = spark.read.json("abfss://" + fileSystemName + "@" + storageAccountName + ".dfs.core.chinacloudapi.cn/small_radio_json.json")

按?SHIFT + ENTER?鍵，運行此塊中的代碼。

運行以下代碼來查看數據幀的內容：

Scala復制

df.show()

會顯示類似于以下代碼片段的輸出：

輸出復制

+---------------------+---------+---------+------+-------------+----------+---------+-------+--------------------+------+--------+-------------+---------+--------------------+------+-------------+------+ | artist| auth|firstName|gender|itemInSession| lastName| length| level| location|method| page| registration|sessionId| song|status| ts|userId| +---------------------+---------+---------+------+-------------+----------+---------+-------+--------------------+------+--------+-------------+---------+--------------------+------+-------------+------+ | El Arrebato |Logged In| Annalyse| F| 2|Montgomery|234.57914| free | Killeen-Temple, TX| PUT|NextSong|1384448062332| 1879|Quiero Quererte Q...| 200|1409318650332| 309| | Creedence Clearwa...|Logged In| Dylann| M| 9| Thomas|340.87138| paid | Anchorage, AK| PUT|NextSong|1400723739332| 10| Born To Move| 200|1409318653332| 11| | Gorillaz |Logged In| Liam| M| 11| Watts|246.17751| paid |New York-Newark-J...| PUT|NextSong|1406279422332| 2047| DARE| 200|1409318685332| 201| ... ...

現(xiàn)在，你已將數據從 Azure Data Lake Storage Gen2 提取到 Azure Databricks 中。

在 Azure Databricks 中轉換數據

原始示例數據?small_radio_json.json?文件捕獲某個電臺的聽眾，有多個不同的列。?在此部分，請對該數據進行轉換，僅檢索數據集中的特定列。

首先，僅從已創(chuàng)建的 dataframe 檢索?firstName?、?lastName?、?gender?、?location?和?level?列。

val specificColumnsDf = df.select("firstname", "lastname", "gender", "location", "level") specificColumnsDf.show()

接收的輸出如以下代碼片段所示：

輸出復制

+---------+----------+------+--------------------+-----+ |firstname| lastname|gender| location|level| +---------+----------+------+--------------------+-----+ | Annalyse|Montgomery| F| Killeen-Temple, TX| free| | Dylann| Thomas| M| Anchorage, AK| paid| | Liam| Watts| M|New York-Newark-J...| paid| | Tess| Townsend| F|Nashville-Davidso...| free| | Margaux| Smith| F|Atlanta-Sandy Spr...| free| | Alan| Morse| M|Chicago-Napervill...| paid| |Gabriella| Shelton| F|San Jose-Sunnyval...| free| | Elijah| Williams| M|Detroit-Warren-De...| paid| | Margaux| Smith| F|Atlanta-Sandy Spr...| free| | Tess| Townsend| F|Nashville-Davidso...| free| | Alan| Morse| M|Chicago-Napervill...| paid| | Liam| Watts| M|New York-Newark-J...| paid| | Liam| Watts| M|New York-Newark-J...| paid| | Dylann| Thomas| M| Anchorage, AK| paid| | Alan| Morse| M|Chicago-Napervill...| paid| | Elijah| Williams| M|Detroit-Warren-De...| paid| | Margaux| Smith| F|Atlanta-Sandy Spr...| free| | Alan| Morse| M|Chicago-Napervill...| paid| | Dylann| Thomas| M| Anchorage, AK| paid| | Margaux| Smith| F|Atlanta-Sandy Spr...| free| +---------+----------+------+--------------------+-----+

可以進一步轉換該數據，將?level?列重命名為?subscription_type?。

Scala復制

val renamedColumnsDF = specificColumnsDf.withColumnRenamed("level", "subscription_type") renamedColumnsDF.show()

接收的輸出如以下代碼片段所示。

+---------+----------+------+--------------------+-----------------+ |firstname| lastname|gender| location|subscription_type| +---------+----------+------+--------------------+-----------------+ | Annalyse|Montgomery| F| Killeen-Temple, TX| free| | Dylann| Thomas| M| Anchorage, AK| paid| | Liam| Watts| M|New York-Newark-J...| paid| | Tess| Townsend| F|Nashville-Davidso...| free| | Margaux| Smith| F|Atlanta-Sandy Spr...| free| | Alan| Morse| M|Chicago-Napervill...| paid| |Gabriella| Shelton| F|San Jose-Sunnyval...| free| | Elijah| Williams| M|Detroit-Warren-De...| paid| | Margaux| Smith| F|Atlanta-Sandy Spr...| free| | Tess| Townsend| F|Nashville-Davidso...| free| | Alan| Morse| M|Chicago-Napervill...| paid| | Liam| Watts| M|New York-Newark-J...| paid| | Liam| Watts| M|New York-Newark-J...| paid| | Dylann| Thomas| M| Anchorage, AK| paid| | Alan| Morse| M|Chicago-Napervill...| paid| | Elijah| Williams| M|Detroit-Warren-De...| paid| | Margaux| Smith| F|Atlanta-Sandy Spr...| free| | Alan| Morse| M|Chicago-Napervill...| paid| | Dylann| Thomas| M| Anchorage, AK| paid| | Margaux| Smith| F|Atlanta-Sandy Spr...| free| +---------+----------+------+--------------------+-----------------+

將數據加載到 Azure Synapse 中

在本部分，請將轉換的數據上傳到 Azure Synapse 中。?使用適用于 Azure Databricks 的 Azure Synapse 連接器直接上傳數據幀，在 Azure Synapse 池中作為表來存儲。

如前所述，Azure Synapse 連接器使用 Azure Blob 存儲作為臨時存儲，以便將數據從 Azure Databricks 上傳到 Azure Synapse。?因此，一開始請?zhí)峁┻B接到存儲帳戶所需的配置。?必須已經按照本文先決條件部分的要求創(chuàng)建了帳戶。

提供從 Azure Databricks 訪問 Azure 存儲帳戶所需的配置。

val blobStorage = "<blob-storage-account-name>.blob.core.chinacloudapi.cn" val blobContainer = "<blob-container-name>" val blobAccessKey = "<access-key>"

指定一個在 Azure Databricks 和 Azure Synapse 之間移動數據時需要使用的臨時文件夾。

val tempDir = "wasbs://" + blobContainer + "@" + blobStorage +"/tempDirs"

運行以下代碼片段，以便在配置中存儲 Azure Blob 存儲訪問密鑰。?此操作可確保不需將訪問密鑰以純文本形式存儲在筆記本中。

val acntInfo = "fs.azure.account.key."+ blobStorage sc.hadoopConfiguration.set(acntInfo, blobAccessKey)

提供連接到 Azure Synapse 實例所需的值。?先決條件是必須已創(chuàng)建 Azure Synapse Analytics 服務。?為 dwServer 使用完全限定的服務器名稱 。?例如，<servername>.database.chinacloudapi.cn?。

//Azure Synapse related settings val dwDatabase = "<database-name>" val dwServer = "<database-server-name>" val dwUser = "<user-name>" val dwPass = "<password>" val dwJdbcPort = "1433" val dwJdbcExtraOptions = "encrypt=true;trustServerCertificate=true;hostNameInCertificate=*.database.chinacloudapi.cn;loginTimeout=30;" val sqlDwUrl = "jdbc:sqlserver://" + dwServer + ":" + dwJdbcPort + ";database=" + dwDatabase + ";user=" + dwUser+";password=" + dwPass + ";$dwJdbcExtraOptions" val sqlDwUrlSmall = "jdbc:sqlserver://" + dwServer + ":" + dwJdbcPort + ";database=" + dwDatabase + ";user=" + dwUser+";password=" + dwPass

運行以下代碼片段來加載轉換的數據幀 renamedColumnsDF ，在 Azure Synapse 中將其存儲為表。?此代碼片段在 SQL 數據庫中創(chuàng)建名為?SampleTable?的表。

spark.conf.set("spark.sql.parquet.writeLegacyFormat","true")renamedColumnsDF.write.format("com.databricks.spark.sqldw").option("url", sqlDwUrlSmall).option("dbtable", "SampleTable") .option( "forward_spark_azure_storage_credentials","True").option("tempdir", tempDir).mode("overwrite").save()

?

連接到 SQL 數據庫，驗證是否看到名為?SampleTable?的數據庫。

運行一個 select 查詢，驗證表的內容。?該表的數據應該與?renamedColumnsDF?dataframe 相同。

總結

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