Ingestion Examples

Anonymization and Casting

SELECT
*
EXCEPT
-- drop some fields
(extra_data, more_extra_data, email_address),
-- type coercion
TRY_CAST(last_updated_at AS DATETIME) AS last_updated_at,
-- PII/PHI masking
TO_HEX(SHA256(email_address)) AS email_address_hash,
FROM
_input
WHERE
-- filter input documents
email_address IS NOT NULL

This query keeps all input fields by default, except for extra_data, more_extra_data, and email_address. It adds two new fields to the final document: last_updated_at and email_address_hash. If there are any input fields named last_updated_at or email_address_hash in the input document, their values in the final document will be the values of the specified expressions, not their values in the input document. It also filters out all input documents where email_address is null.

Data Clustering

SELECT cntry AS country, cont AS continent, capt AS capital, gdp_usd as gross_domestic_product, ROUND(population / 1e6) AS population_milliions
FROM _input
WHERE population_millions > 0
CLUSTER BY continent, country

This query drops all input fields by default since there is no * in the SELECT clause, and instead it explicitly renames several input fields to their cleaner final names country, continent, capital, gross_domestic_product and computes pouplation_millions from the input field population. The WHERE clause filters out any documents corresponding to countries with a population less than 1M. And data clustering is configured on the Collection with clustering key (continent, country) which will speed up queries that filter on continent, or continent and country significantly.

CDC Control Records and _op

SELECT
    user_id AS _id,
    IF(_input.header."delete" = true, 'DELETE', 'UPSERT') AS _op,
    IF(_input.header."delete" = true, null, PARSE_TIMESTAMP('%Y-%m-%d %H:%M:%E*S', created_at_ts)) AS _event_time,
    * EXCEPT (user_id, header, created_at_ts)
FROM _input

This query maps user_id from the source documents to _id in Rockset and interprets _op based on whether a field is set in the header. In the case of a new record coming in, header.delete will be false (or null) and both IF statements will execute their second branch which will set _op = 'UPSERT' and will parse _event_time from _created_at_ts. All fields except the mapped ones and the header will then be inserted into Rockset. When a delete comes through and header.delete is true, then the first branch of the IF statements will execute which will set _op = DELETE and leave _event_time as null. This will issue a delete for the document corresponding to _id.

Precomputing Fields

SELECT
twitter_handle,
follower_count,
-- search tokenization
TOKENIZE(tweet_text, 'en_US') AS tweet_text_tokens,
-- functional index
REGEXP_EXTRACT_ALL(
    email_address,
    '^([a-zA-Z0-9_.+-]+)@([a-zA-Z0-9-]+\.[a-zA-Z0-9-.]+$)',
    2
) AS email_address_domain,
-- native geography type
ST_GEOGPOINT(longitude, latitude) AS geo,
FROM _input

This query drops all input fields by default and only keeps the input fields twitter_handle and follower_count. It also adds three new fields to our final document: tweet_text_tokens, email_address_domain, and geo, each of which can be used to speed up queries that would otherwise have to run expensive operations at query time on the raw input fields.

Using UNDEFINED

SELECT
*,
IF(user IS NOT NULL, CONCAT(user, '@rockset.com'), UNDEFINED) AS email_address
FROM _input

This query keeps all input fields by default and adds one new field to the final document: email_address.

🚧

If user is null, the email_address field will be set to undefined in the final document.

Setting a field’s value to undefined in an ingest transformation means that the field will not be present in the final document. Thus, email_address will only be present in the final document if the input document’s user field is not null. See documentation on undefined for more details.