Snowpark Migration Accelerator: Unterstützte Plattformen

Unterstützte Plattformen

The Snowpark Migration Accelerator (SMA) currently supports the following programming languages as source code:

  • Python

  • Scala

  • SQL

The SMA analyzes both code files and notebook files to identify any usage of Spark API and other third-party APIs. For a complete list of file types that SMA can analyze, please refer to Supported Filetypes.

SQL-Dialekte

Der Snowpark Migration Accelerator (SMA) kann Codedateien analysieren, um SQL-Elemente zu identifizieren. Derzeit kann SMA SQL-Code erkennen, der in den folgenden Formaten geschrieben wurde:

  • Spark SQL

  • Hive QL

  • Databricks SQL

SQL Assessment and Conversion Guidelines

Obwohl Spark SQL und Snowflake SQL in hohem Maße kompatibel sind, kann es vorkommen, dass SQL-Code nicht perfekt konvertiert wird.

SQL analysis is only possible when the SQL is received in the following ways:

  • A SQL cell within a supported notebook file

  • A .sql or .hql file

  • A complete string passed to a spark.sql statement.

    Some variable substitutions are not supported. Here are a few examples:

    • Parsed:

      spark.sql("select * from TableA")
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      New SMA scenarios supported include the following:

      # explicit concatenation
spark.sql("select * from TableA" + ' where col1 = 1')

# implicit concatenation (juxtaposition)
spark.sql("select * from TableA" ' where col1 = 1')

# var initialized with sql in previous lines before execution on same scope
sql = "select * from TableA"
spark.sql(sql)

# f-string interpolation:
spark.sql(f"select * from {varTableA}")

# format kindof interpolation
spark.sql("select * from {}".format(varTableA))

# mix var with concat and f-string interpolation
sql = f"select * from {varTableA} " + f'where {varCol1} = 1'
spark.sql(sql)
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    • Not Parsed:

      some_variable = "TableA"
spark.sql("select * from" + some_variable)
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    SQL elements are accounted for in the object inventories, and a readiness score is generated specifically for SQL.

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