Some Date and Timestamp Values Are Wrong by Several Days Time zones can also be incorrect in Parquet data, but the reason is different. +-+-+-+-+-ĮXECUTION | ORC_FILE_INFO | ORC file does not have writer timezone information | OrcParser | Timestamp values in the ORC source will be computed using local timezone | 2 GROUP BY event_category, event_type, event_description, operator_name, event_detailsĮvent_category | event_type | event_description | operator_name | event_details | count => SELECT event_category, event_type, event_description, operator_name, event_details, COUNT(event_type)ĪS COUNT FROM QUERY_EVENTS WHERE event_type ILIKE 'ORC_FILE_INFO' The first time you query a new ORC data source, you should query this table to look for missing time zone information: If the file does not contain a time zone, Vertica uses the local time zone and logs an ORC_FILE_INFO event in the QUERY_EVENTS system table. If the file was written with an older version of the library, the time zone is missing from the file. Vertica looks for this value and applies it when loading timestamps. When writing timestamps, the ORC library now records the time zone in the stripe footer. The behavior of this library changed with Hive version 1.2.0, so timestamp representation depends on what version was used to write the data. Vertica and Hive both use the Apache ORC library to interact with ORC data. For ORC Data, Time Zones in Timestamp Values Are Not Correct Time zones can also be incorrect in ORC data, but the reason is different. When creating the table in Vertica, you can avoid this issue by using the TIMESTAMPTZ data type instead of TIMESTAMP. WARNING 0: SQL TIMESTAMPTZ is more appropriate for Parquet TIMESTAMP When this situation occurs, Vertica produces a warning at query time such as the following: If you define the column in your table with the TIMESTAMP data type, Vertica interprets timestamps read from Parquet files as values in the local time zone. Reading timestamps from a Parquet file in Vertica might result in different values, based on the local time zone. This issue occurs because the Parquet format does not support the SQL TIMESTAMP data type. For Parquet Data, Time Zones in Timestamp Values Are Not Correct To avoid this problem, add the missing columns to your table definition. When you load data from Hadoop native file formats, your table must consume all of the data in the file, or this error results. CREATE TABLE nation (nationkey bigint, name varchar(500),ĮRROR 7087: Attempt to load 4 columns from an orc source
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