Convert Mysql Query into Elastic search query - php

Question

i'm working on elastic search but not expert in making elastic search queries. find my query bellow and if possible to convert into elasticsearch query then take thanks in advance
SELECT
`currency`.`id` AS `cur_id`,
`currency`.`currency_name` AS `cur_name`,
`currency`.`currency_code` AS `cur_code`,
`currency`.`currency_slug` AS `cur_slug`,
`currency`.`logo` AS `cur_logo`,
`currency`.`added_date` AS `cur_added_date`,
`currency`.`mineable_or_not` AS `mineable_or_not`,
`currency`.`market_cap` AS `cur_market_cap`,
`currency`.`circulating_supply` AS `cur_circulating_supply`,
`currency`.`max_supply` AS `cur_max_supply`,
`currency`.`total_supply` AS `cur_total_supply`,
`currency`.`market_cap` AS `ng_cur_market_cap`,
`currency`.`added_date` AS `ng_cur_added_date`,
`currency`.`circulating_supply` AS `ng_cur_circulating_supply`,
`calculations`.`volume_1hour` AS `cal_volume_1hour`,
`calculations`.`volume_24hour` AS `cal_volume_24hour`,
`calculations`.`volume_168hour` AS `cal_volume_168hour`,
`calculations`.`volume_720hour` AS `cal_volume_720hour`,
`calculations`.`volume_24hour_btc` AS `cal_volume_24hour_btc`,
`calculations`.`current_price` AS `cal_current_price`,
`calculations`.`percentage_change` AS `cal_percentage_change_24h`,
`calculations`.`percentage_change_1h` AS `cal_percentage_change_1h`,
`calculations`.`percentage_change_168h` AS `cal_percentage_change_168h`,
`calculations`.`volume_24hour` AS `ng_cal_volume_24hour`,
`calculations`.`current_price` AS `ng_cal_current_price`
FROM `currency`
JOIN `calculations` ON `calculations`.`currency_id` = `currency`.`id`
WHERE `calculations`.`update_status` = 1 AND `currency`.`currency_type` != 3 AND `calculations`.`update_status` = 1 AND `currency`.`status` = 1
ORDER BY `market_cap` DESC
LIMIT 100

Answer 1

As eliasah commented, there is no join operation in elastic search.
Joining queries
In general you can't really perform joining queries in ES. You can have a parent/child relationship on documents that are under the same index, but that is something I would not opt into. My best advice is to denormalize your data and have each document as 'self-contained' as possible. In this specific example, one possible solution is to store the calculations inside the currency, you would end up with a query like:
{
"_source": ["id", "logo", ..., "calculations.volume_1h","calculations.volume_24h",...],
"query": {
"bool": {
"must":[
{
"match":{
"calculations.update_status":1
}
},
{
"match":{
"currency_type":3
}
},
{
"match":{
"status":1
}
}
]
},
"sort" : [
{
"market_cap": {
"order": "desc"
}
}
]
"size":100
}