使用 Synapse Analytics 将数据框写入 SQL 专用数据库

Question

我想从我的 Azure Data Lake Storage Gen2 加载数据帧并将其写入 SQL 我在 Synapse 中创建的专用数据库。

这是我所做的：

df = spark.read.format("delta").load(BronzePath)
df.write.format("com.databricks.spark.sqldw").option("url", jdbcUrl).save()

我有以下错误：

java.lang.ClassNotFoundException: Failed to find data source: com.databricks.spark.sqldw.

正在做：

df.write.mode("overwrite").saveAsTable("MyTable")

在 Spark 默认数据库（蓝色十字）中创建 table。那不是我需要的。我想将我的 table 放入专用数据库（蓝色箭头）：

Answer 1

Post 更多代码，包括 jdbc url，如果它不同于 this guide。我没有在 conf 中看到设置存储密钥的代码，你似乎也在使用不同的方式来保存。


# Otherwise, set up the Blob storage account access key in the notebook session conf.
spark.conf.set(
  "fs.azure.account.key.<your-storage-account-name>.blob.core.windows.net",
  "<your-storage-account-access-key>")

# Get some data from an Azure Synapse table.
df = spark.read \
  .format("com.databricks.spark.sqldw") \
  .option("url", "jdbc:sqlserver://<the-rest-of-the-connection-string>") \
  .option("tempDir", "wasbs://<your-container-name>@<your-storage-account-name>.blob.core.windows.net/<your-directory-name>") \
  .option("forwardSparkAzureStorageCredentials", "true") \
  .option("dbTable", "<your-table-name>") \
  .load()

# Load data from an Azure Synapse query.
df = spark.read \
  .format("com.databricks.spark.sqldw") \
  .option("url", "jdbc:sqlserver://<the-rest-of-the-connection-string>") \
  .option("tempDir", "wasbs://<your-container-name>@<your-storage-account-name>.blob.core.windows.net/<your-directory-name>") \
  .option("forwardSparkAzureStorageCredentials", "true") \
  .option("query", "select x, count(*) as cnt from table group by x") \
  .load()

# Apply some transformations to the data, then use the
# Data Source API to write the data back to another table in Azure Synapse.

df.write \
  .format("com.databricks.spark.sqldw") \
  .option("url", "jdbc:sqlserver://<the-rest-of-the-connection-string>") \
  .option("forwardSparkAzureStorageCredentials", "true") \
  .option("dbTable", "<your-table-name>") \
  .option("tempDir", "wasbs://<your-container-name>@<your-storage-account-name>.blob.core.windows.net/<your-directory-name>") \
  .save()

另读

Supported save modes for batch writes 和
Write semantics 在常见问题解答中。

creates the table in Spark default database (blue cross). That is not what I need. I want to have my table in the dedicated database (blue arrow):

如所述here “Spark 将为您创建一个默认的本地 Hive Metastore（使用 Derby）。”

所以当你不给它一个 path/jdbcurl (df.write.mode("overwrite").saveAsTable("MyTable")) 时，它会保存到本地 Hive。

使用 Synapse Analytics 将数据框写入 SQL 专用数据库

Write dataframe to SQL dedicated database using Synapse Analytics

pyspark

apache-spark-sql

azure-synapse