Understanding Amazon Athena Partitioning Query Errors

When working with Amazon Athena, creating a partitioned external table can be a powerful way to analyze and process large datasets. However, there are times when the query might fail due to various reasons such as incorrect syntax or incompatible configurations. In this article, we’ll delve into the specifics of Amazon Athena’s partitioning queries, explore common pitfalls, and provide practical advice on how to troubleshoot and resolve errors.

Introduction to Amazon Athena Partitioning

Amazon Athena is a fast, cloud-powered SQL-like query engine that allows users to analyze data stored in S3. Its partitioning feature enables users to split large datasets into smaller, more manageable chunks based on specific criteria. This approach significantly improves query performance by reducing the amount of data being processed.

When creating an external table using Amazon Athena’s partitioning feature, you must specify the following:

• The CREATE EXTERNAL TABLE statement
• The ROW FORMAT SERDE clause, which specifies the serialization format for each row
• The WITH serdeproperties clause, which defines additional properties for the serialization format
• The PARTITIONED BY clause, which specifies the partitioning criteria
• The STORED AS parquet clause, which indicates that the data should be stored in a Parquet file format

Common Partitioning Query Errors

In the provided Stack Overflow question, the user encounters an error message with the code “no viable alternative at input ‘create external’”. This error typically occurs when there’s a conflict between two or more clauses in the CREATE EXTERNAL TABLE statement.

Clause Conflicts

The main culprit behind this error is often the conflicting ROW FORMAT SERDE and STORED AS parquet clauses. The ROW FORMAT SERDE specifies the serialization format for each row, while the STORED AS parquet clause indicates that the data should be stored in a Parquet file format.

When both clauses are present, Athena can’t determine which one takes precedence, leading to an error.

Solution: Removing Conflicting Clauses

To resolve this issue, you need to remove one of the conflicting clauses. Here’s how:

• Remove the ROW FORMAT SERDE clause if you’re using Parquet as the storage format.
• Remove the STORED AS parquet clause if you’re not using a specific serialization format.

Here’s an example of the corrected code without the ROW FORMAT SERDE clause:

CREATE EXTERNAL TABLE access_data (
    `Date` DATE,
    Time STRING,
    Location STRING,
    Bytes INT,
    RequestIP STRING,
    Host STRING,
    Uri STRING,
    Status INT,
    Referrer STRING,
    os STRING,
    Browser STRING,
    BrowserVersion STRING 
)
PARTITIONED BY (dt DATE) STORED AS parquet LOCATION 's3://[source bucket]/';

Or here’s an example with the STORED AS parquet clause removed:

CREATE EXTERNAL TABLE access_data (
    `Date` DATE,
    Time STRING,
    Location STRING,
    Bytes INT,
    RequestIP STRING,
    Host STRING,
    Uri STRING,
    Status INT,
    Referrer STRING,
    os STRING,
    Browser STRING,
    BrowserVersion STRING 
)
ROW FORMAT SERDE 'org.apache.hive.hcatalog.data.JsonSerDe'
WITH serdeproperties ( 'paths'='`Date`,Time, Uri' )
PARTITIONED BY (dt DATE);

Conclusion

In conclusion, Amazon Athena’s partitioning queries can be complex and prone to errors due to conflicting clauses. By understanding the causes of these errors and following best practices for creating external tables, you can avoid common pitfalls like clause conflicts.

When encountering an error message, carefully review your query syntax and identify any conflicting clauses. Removing one of the conflicting clauses is often a straightforward solution that resolves the issue.

By mastering Amazon Athena’s partitioning features, you’ll be better equipped to handle large datasets and optimize performance for your queries.

Last modified on 2025-01-10