sql := `SELECT COUNT(*), MAX(colA) FROM myTable WHERE colB < 10 GROUP BY colC HAVING COUNT(*) > 20`
e := NewESql()
dsl, _, err := e.ConvertPretty(sql)    // convert sql to dsl
if err == nil {
    fmt.Println(dsl)
}

Custom Query Macro

ESQL support API ProcessQueryKey to register custom policy for colName replacement. It accepts 2 functions, the first function determines whether a colName is to be replaced, the second specifies how to do the replacement. Use case: user has custom field field, but to resolve confict, server stores the field as Custom.field. ProcessQueryKey API can automatically do the conversion.

ESQL support API ProcessQueryValue to register custom policy for value processing. It accepts 2 functions, the first function determines whether a value of a colName is to be processed, the second specifies how to do the processing. Use case: user want to query time in readable format, but server stores time as an integer (unix nano). ProcessQueryValue API can automatically do the conversion.

Below shows an example.

sql := "SELECT colA FROM myTable WHERE colB < 10 AND dateTime = '2015-01-01T02:59:59Z'"
// custom policy that change colName like "col.." to "myCol.."
func myKeyFilter(colName string) bool {
    return strings.HasPrefix(colName, "col")
}
func myKeyProcess(colName string) (string, error) {
    return "myCol"+colName[3:], nil
}
// custom policy that convert formatted time string to unix nano
func myValueFilter(colName string) bool {
    return strings.Contains(colName, "Time") || strings.Contains(colName, "time")
}
func myValueProcess(timeStr string) (string, error) {
    // convert formatted time string to unix nano integer
    parsedTime, _ := time.Parse(defaultDateTimeFormat, timeStr)
    return fmt.Sprintf("%v", parsedTime.UnixNano()), nil
}
// with the 2 policies , converted dsl is equivalent to
// "SELECT myColA FROM myTable WHERE myColB < 10 AND dateTime = '1561678568048000000'
// in which the time is in unix nano format
e := NewESql()
e.ProcessQueryKey(myKeyFilter, myKeyProcess)            // set up macro for key
e.ProcessQueryValue(myValueFilter, myValueProcess)      // set up macro for value
dsl, _, err := e.ConvertPretty(sql)                     // convert sql to dsl
if err == nil {
    fmt.Println(dsl)
}

Pagination

ESQL support 2 kinds of pagination: FROM keyword and ES search_after.

FROM keyword: the same as SQL syntax. Be careful, ES only support a page smaller than 10k, if your offset is large than 10k, search_after is necessary.
search_after: Once you know the paging tokens, just feed them to Convert or ConvertPretty API in order.

Below shows an example.

// first page
sql_page1 := "SELECT * FROM myTable ORDER BY colA, colB LIMIT 10"
e := NewESql()
dsl_page1, sortFields, err := e.ConvertPretty(sql_page1)

// second page
// 1. Use FROM to retrieve the 2nd page
sql_page2_FROM := "SELECT * FROM myTable ORDER BY colA, colB LIMIT 10 FROM 10"
dsl_page2_FROM, sortFields, err := e.ConvertPretty(sql_page2_FROM)

// 2. Use search_after to retrieve the 2nd page
// we can use sortFields and the query result from page 1 to get the page tokens
sql_page2_search_after := sql_page1
page_token_colA := "123"
page_token_colB := "bbc"
dsl_page2_search_after, sortFields, err := e.ConvertPretty(sql_page2_search_after, page_colA, page_colB)

For Cadence usage, refer to this link.

ES V2.x vs ES V6.5

Item	ES V2.x	ES v6.5
missing check	{"missing": {"field": "xxx"}}	{"must_not": {"exist": {"field": "xxx"}}}
group by multiple columns	nested "aggs" field	"composite" flattened grouping

Attentions

If you want to apply aggregation on some fields, they should not be in type text in ES
COUNT(colName) will include documents w/ null values in that column in ES SQL API, while in esql we exclude null valued documents
ES SQL API and esql do not support SELECT DISTINCT, a workaround is to query something like SELECT * FROM table GROUP BY colName
ES SQL API does not support ORDER BY aggregation, esql support it by applying bucket_sort
ES SQL API does not support HAVING aggregation that not show up in SELECT, esql support it
To use regex query, the column should be keyword type, otherwise the regex is applied to all the terms produced by tokenizer from the original text rather than the original text itself
Comparison with arithmetics can be potentially slow since it uses scripting query and thus is not able to take advantage of reverse index. For binary operators, please refer to this link on the precedence. We don't support all of them.
Comparison with arithmetics does not support date type

Acknowledgement

This project is originated from elasticsql. Table below shows the improvement.

Item	detail
comparison	support comparison with arithmetics of different columns
keyword IS	support standard SQL keywords IS NULL, IS NOT NULL for missing check
keyword NOT	support NOT, convert NOT recursively since elasticsearch's must_not is not the same as boolean operator NOT in sql
keyword LIKE	using "wildcard" tag, support SQL wildcard '%' and '_'
keyword REGEX	using "regexp" tag, support standard regular expression syntax
keyword GROUP BY	using "composite" tag to flatten multiple grouping
keyword ORDER BY	using "bucket_sort" to support order by aggregation functions
keyword HAVING	using "bucket_selector" and painless scripting language to support HAVING
aggregations	allow introducing aggregation functions from all HAVING, SELECT, ORDER BY
column name filtering	allow user pass an white list, when the sql query tries to select column out side white list, refuse the converting
column name replacing	allow user pass an function as initializing parameter, the matched column name will be replaced upon the policy
query value replacing	allow user pass an function as initializing parameter, query value will be processed by such function if the column name matched in filter function
pagination	also return the sorting fields for future search after usage
optimization	using "filter" tag rather than "must" tag to avoid scoring analysis and save time
optimization	no redundant {"bool": {"filter": xxx}} wrapped
optimization	does not return document contents in aggregation query
optimization	only return fields user specifies after SELECT