Parsing dates can be tricky, especially with varied date formats from different apps and user input. Incorrectly parsed dates are a common root cause for incidents and incorrect data analysis. This post covers best practices for parsing dates in ClickHouse, focusing on the parseDateTimeBestEffortOrNull function, your new Swiss army knife when it comes to parsing dates.

The parseDateTimeBestEffortOrNull function

When it comes to parsing dates in ClickHouse, the parseDateTimeBestEffortOrNull function is the way to go. It's versatile, reliable, and can handle a ton of date and time formats. Let's break it down.

Syntax and arguments

This function converts a string date/time into a DateTime data type. If it can't recognize the format, it returns NULL instead of throwing a tantrum (error).

Syntax:

parseDateTimeBestEffortOrNull(time_string [, time_zone])

Arguments:

• time_string: The date/time string you want to convert. Required.
• time_zone: Optional. If you don't specify, it uses the server's default time zone.

Error handling

One of the best things about parseDateTimeBestEffortOrNull is its error handling. Instead of crashing your query, it just returns NULL for unrecognized formats. This is super handy when you're dealing with messy data from multiple sources.

Supported Date Formats

This function is a date-format ninja. It can handle:

• ISO 8601: 2020-12-12T17:36:00Z
• RFC 1123: Sat, 18 Aug 2018 07:22:16 GMT
• Unix Timestamps: 1284101485
• Common Date-Time Formats: YYYY-MM-DD hh:mm:ss, DD/MM/YYYY hh:mm:ss, YYYYMMDDhhmmss
• Dates Without Time Components: YYYY, YYYY-MM, DD/MM/YYYY
• Dates with Time Zone Offsets: 2020-12-12 17:36:00 -5:00
• Syslog Timestamps: Jun 9 14:20:32

Examples

Let's see it in action:

ISO 8601 format:

SELECT parseDateTimeBestEffortOrNull('2024-08-12T17:36:00Z') AS parsed_date;

Result:

┌─parsed_date───────────────┐
│ 2024-08-12 17:36:00       │
└───────────────────────────┘

RFC 1123 format:

SELECT parseDateTimeBestEffortOrNull('Sat, 18 Aug 2024 07:22:16 GMT') AS parsed_date;

Result:

┌─parsed_date───────────────┐
│ 201824-08-18 07:22:16     │
└───────────────────────────┘

Unix timestamp:

SELECT parseDateTimeBestEffortOrNull('1284101485') AS parsed_date;

Result:

┌─parsed_date───────────────┐
│ 2010-09-10 06:51:25       │
└───────────────────────────┘

Common date-time format:

SELECT parseDateTimeBestEffortOrNull('2024-08-12 17:36:00') AS parsed_date;

Result:

┌─parsed_date───────────────┐
│ 2024-08-12 17:36:00       │
└───────────────────────────┘

Date with time zone offset:

SELECT parseDateTimeBestEffortOrNull('2024-12-12 17:36:00 -5:00') AS parsed_date;

Result:

┌─parsed_date───────────────┐
│ 2024-12-12 22:36:00       │
└───────────────────────────┘

Date parsing functions explained

Let's dive into the parseDateTimeBestEffort family and see how they stack up against the usual suspects like toDate and toDateTime.

parseDateTimeBestEffortOrNull vs. parseDateTimeBestEffort

parseDateTimeBestEffortOrNull: Tries to parse your date string. If it fails, it just returns NULL. Handy for when your data is a bit of a hot mess.

SELECT parseDateTimeBestEffortOrNull('invalid-date') AS parsed_date;

Result:

┌─parsed_date─┐
│        NULL │
└─────────────┘

parseDateTimeBestEffort: Similar, but if it can't parse the date, it throws an error. Use this when you need to keep your data squeaky clean.

SELECT parseDateTimeBestEffort('invalid-date') AS parsed_date;

Result:

Received exception from server (version 24.8.4):
Code: 41. DB::Exception: Received from localhost:9000. DB::Exception: Cannot read DateTime: unexpected word: In scope SELECT parseDateTimeBestEffort('invalid-date') AS parsed_date. (CANNOT_PARSE_DATETIME)
(query: SELECT parseDateTimeBestEffort('invalid-date') AS parsed_date;)

parseDateTimeBestEffortOrZero

parseDateTimeBestEffortOrZero: When parsing fails, parseDateTimeBestEffortOrZero falls back to the “zero” date, which in ClickHouse is the Unix epoch start date—”1970-01-01 00:00:00”.

SELECT parseDateTimeBestEffortOrZero('invalid-date') AS parsed_date;

Result:

┌─parsed_date───────────────┐
│ 1970-01-01 00:00:00       │
└───────────────────────────┘

parseDateTimeBestEffortUS

parseDateTimeBestEffortUS: Tailored for US date formats like MM/DD/YYYY. Perfect for when your data is as American as apple pie.

SELECT parseDateTimeBestEffortUS('12/31/2024') AS parsed_date;

Result:

┌─parsed_date───────────────┐
│ 2024-12-31 00:00:00       │
└───────────────────────────┘

parseDateTime32BestEffort and parseDateTime64BestEffort

parseDateTime32BestEffort and parseDateTime64BestEffort: These functions are similar to parseDateTimeBestEffort, but they return DateTime32 and DateTime64 data types respectively. They're useful when you need more precision or a wider range of dates.

parseDateTime32BestEffort:

SELECT parseDateTime32BestEffort('2024-12-31 23:59:59') AS parsed_date;

Result:

┌─parsed_date───────────────┐
│ 2024-12-31 23:59:59       │
└───────────────────────────┘

parseDateTime64BestEffort:

SELECT parseDateTime64BestEffort('2024-12-31 23:59:59.123456', 6) AS parsed_date;

Result:

┌───────────────parsed_date──┐
│ 2024-12-31 23:59:59.123456 │
└────────────────────────────┘

Note that parseDateTime64BestEffort takes an additional precision parameter (6 in this case) to specify the number of decimal places for fractional seconds.

These functions are particularly useful when dealing with high-precision timestamps or when you need to store dates outside the range of the standard DateTime type.

parseDateTime

parseDateTime: Converts a string to DateTime but needs the format to be YYYY-MM-DD hh:mm:ss. Less flexible but solid for consistent data.

SELECT parseDateTime('2024-12-31 23:59:59') AS parsed_date;

Result:

┌─parsed_date───────────────┐
│ 2024-12-31 23:59:59       │
└───────────────────────────┘

Parsing dates in Materialized Views

Parsing dates in semi-structured data like JSON can be a real headache. Luckily, ClickHouse’s parseDateTimeBestEffortOrNull function is here to save the day. Let’s dive into how you can use it in materialized views to make date parsing a breeze.

Safely cast dates and timestamps

JSON dates can be all over the place in terms of format. With parseDateTimeBestEffortOrNull, you can safely cast these dates and timestamps, ensuring they’re correctly interpreted and stored.

CREATE MATERIALIZED VIEW mv_parsed_dates
ENGINE = MergeTree()
AS
SELECT
    parseDateTimeBestEffortOrNull(JSONExtractString(json_col, 'timestamp')) AS parsed_date,
    other_column_1,
    other_column_2
FROM source_table;

This view extracts the timestamp field from a JSON column and parses it. If parsing fails, it stores NULL, so you can handle these cases without breaking a sweat.

Combining parseDateTimeBestEffortOrNull with other functions

Need to juggle multiple date formats? No problem. Combine parseDateTimeBestEffortOrNull with other ClickHouse functions to handle various date formats in the same dataset.

CREATE MATERIALIZED VIEW mv_combined_dates
ENGINE = MergeTree()
AS
SELECT
    parseDateTimeBestEffortOrNull(JSONExtractString(json_col, 'date1')) AS parsed_date1,
    parseDateTimeBestEffortOrNull(JSONExtractString(json_col, 'date2')) AS parsed_date2,
    other_column
FROM source_table;

Here, two different date fields are extracted and parsed, ensuring both are correctly handled no matter their formats.

Using Materialized Views to preprocess and store parsed dates

Materialized views can preprocess and store parsed dates, making your main queries faster and more efficient. Do the heavy lifting upfront so your queries can run like a well-oiled machine.

CREATE MATERIALIZED VIEW mv_preprocessed_dates
ENGINE = MergeTree()
AS
SELECT
    parseDateTimeBestEffortOrNull(date_string) AS parsed_date,
    other_columns
FROM raw_data_table;

This view preprocesses the date parsing, storing the results for future queries to use. Your queries will thank you for the performance boost.

Conclusion

Parsing dates can feel like wrestling a bear, but with the right tools, it’s more like a friendly arm-wrestle. We’ve covered why accurate date parsing is crucial, how versatile the parseDateTimeBestEffortOrNull function is, and how to use it effectively.

Key points recap:

1. Why date parsing matters: Accurate date parsing is key for stable data applications and business decisions. Mess it up, and you’re looking at incidents, misleading data, and bad outcomes.
2. parseDateTimeBestEffortOrNull rocks: This function handles a ton of date formats and returns NULL for unrecognized ones, making it robust and error-tolerant.
3. Parsing function showdown: We compared parseDateTimeBestEffortOrNull with other parsing functions like parseDateTimeBestEffort, parseDateTimeBestEffortOrZero, and parseDateTimeBestEffortUS. Each has its own quirks and use cases.
4. Materialized Views FTW: Use materialized views to preprocess and store parsed dates. This boosts query performance and keeps things consistent.

Implementing parseDateTimeBestEffortOrNull in your ClickHouse queries can make your date parsing life a lot easier. It handles diverse date formats and returns NULL for the weird ones, so your queries don’t crash and burn.

TheparseDateTimeBestEffortOrNull function is all you need to parse dates in ClickHouse 😀.

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