Clickhouse join with condition - sql
I found strange thing, the query:
SELECT *
FROM progress as pp
ALL LEFT JOIN links as ll USING (viewId)
WHERE viewId = 'a776a2f2-16ad-448a-858d-891e68bec9a8'
Result: 0 rows in set. Elapsed: 5.267 sec. Processed 8.62 million rows, 484.94 MB (1.64 million rows/s., 92.08 MB/s.)
Here modified query:
SELECT *
FROM
(SELECT *
FROM progress
WHERE viewId = 'a776a2f2-16ad-448a-858d-891e68bec9a8') AS p ALL
LEFT JOIN
(SELECT *
FROM links
WHERE viewId = toUUID('a776a2f2-16ad-448a-858d-891e68bec9a8')) AS l ON p.viewId = l.viewId;
Result : 0 rows in set. Elapsed: 0.076 sec. Processed 4.48 million rows, 161.35 MB (58.69 million rows/s., 2.12 GB/s.)
But it looks dirty.
Isn't it supposed to optimize the query considering where condition?
What is the right way to write the query here, and what if it will be where in?
Then I try to add another join:
SELECT *
FROM
(SELECT videoUuid AS contentUuid,
viewId
FROM
(SELECT *
FROM progress
WHERE viewId = 'a776a2f2-16ad-448a-858d-891e68bec9a8') p ALL
LEFT JOIN
(SELECT *
FROM links
WHERE viewId = toUUID('a776a2f2-16ad-448a-858d-891e68bec9a8')) USING `viewId`) ALL
LEFT JOIN `metaInfo` USING `viewId`,
`contentUuid`;
The result again very slow, considering that I want just join 3 tables with condition selection one row:
0 rows in set. Elapsed: 1.747 sec. Processed 9.13 million rows, 726.55 MB (5.22 million rows/s., 415.85 MB/s.)
At this moment the CH not very good cope with multi-joins queries (DB star-schema) and the query optimizer not good enough to rely on it completely.
So it needs to explicitly say how to 'execute' a query by using subqueries instead of joins.
Consider the test query:
SELECT table_01.number AS r
FROM numbers(87654321) AS table_01
INNER JOIN numbers(7654321) AS table_02 ON (table_01.number = table_02.number)
INNER JOIN numbers(654321) AS table_03 ON (table_02.number = table_03.number)
INNER JOIN numbers(54321) AS table_04 ON (table_03.number = table_04.number)
WHERE r = 54320
/*
┌─────r─┐
│ 54320 │
└───────┘
1 rows in set. Elapsed: 6.261 sec. Processed 96.06 million rows, 768.52 MB (15.34 million rows/s., 122.74 MB/s.)
*/
Let's rewrite it using subqueries to significantly speed it up.
SELECT number AS r
FROM numbers(87654321)
WHERE r = 54320 AND number IN (
SELECT number AS r
FROM numbers(7654321)
WHERE r = 54320 AND number IN (
SELECT number AS r
FROM numbers(654321)
WHERE r = 54320 AND number IN (
SELECT number AS r
FROM numbers(54321)
WHERE r = 54320
)
)
)
/*
┌─────r─┐
│ 54320 │
└───────┘
1 rows in set. Elapsed: 0.481 sec. Processed 96.06 million rows, 768.52 MB (199.69 million rows/s., 1.60 GB/s.)
*/
There are other ways to optimize JOIN:
use External dictionary to get rid of join on 'small'-table
use Join table engine
use ANY-strictness
use specific settings like join_algorithm, partial_merge_join_optimizations etc
Some useful refs:
Altinity webinar: Tips and tricks every ClickHouse user should know
Altinity webinar: Secrets of ClickHouse Query Performance
Isn't it supposed to optimize the query concidering where condition?
Such optimization is not implemented yet
It is expected behavior.
According to CH doc https://clickhouse.tech/docs/en/sql-reference/statements/select/join/#performance "When running a JOIN, there is no optimization of the order of execution in relation to other stages of the query. The join (a search in the right table) is run before filtering in WHERE and before aggregation."
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Your queries are quite different. In the first, the where clause is part of the SQL statement passed to OPENQUERY(). This has two important effects: The amount of data returned is much smaller, only being the rows that match the condition. The query can be optimized with the WHERE clause. If you need to share the table, I might suggest that you make a copy on the local server -- either using replication or scheduling a job to copy it over.
SQL query Optimisation JOIN multiple column
I have two tables on Microsoft Access: T_DATAS (about 200 000 rows) and T_REAF (about 1000 rows). T_DATAS has a lot of columns (about 30 columns) and T_REAF has about 10 columns. I have to tell you that I am not allowed to change those tables nor to create other tables. I have to work with it. Both tables have 6 columns that are the same. I need to join the tables on these 6 columns, to select ALL the columns from T_DATAS AND the columns that are in T_REAF but not in T_DATAS. My query is : SELECT A.*, B.CARROS_NEW, B.SEGT_NEW, B.ATTR INTO FINALTABLE FROM T_DATAS A LEFT JOIN T_REAF B ON A.REGION LIKE B.REGION AND A.PAYS LIKE B.PAYS AND A.MARQUE LIKE B.MARQUE AND A.MODELE LIKE B.MODELE AND A.CARROS LIKE B.CARROS AND A.SEGT LIKE B.SEGT I have the result I need but the problem is that this query is taking way too long to give the result (about 3 minutes). I know that T_DATAS contains a lot of rows (200 000) but I think that 3 minutes is too long for this query. Could you please tell me what is wrong with this query? Thanks a lot for your help
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I assume that those 6 columns are same may have same datatype also. Note: Equals (=) operator is a comparison operator - that compares two values for equality. So in your query replace LIKE with = and see the result time. SELECT A.* ,B.CARROS_NEW ,B.SEGT_NEW ,B.ATTR INTO FINALTABLE FROM T_DATAS A LEFT JOIN T_REAF B ON A.REGION = B.REGION AND A.PAYS = B.PAYS AND A.MARQUE = B.MARQUE AND A.MODELE = B.MODELE AND A.CARROS = B.CARROS AND A.SEGT = B.SEGT
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Rebuild indexes on all the tables involved in the query. Run the query again and check time. It will decrease the execution time. I will update you soon with tuned query if I can. Keep Querying!
Slow ORDER BY in large table
I have problem with ORDER BY clause. When I remove ORDER BY in following query, query is finished in 0.004 seconds. If I keep it, query is running very slow = 56 seconds. It is because MySQL is first grabbing all 500 000 records, then sorting and finally returing only first 18 records. How can I solve this big table ordering problem ? Thanks. Explain: http://img444.imageshack.us/img444/9440/explain.png SQL Query: SELECT `_sd`.`sazbaDPHId`, `_sd`.`sazbaDPH`, `_sd`.`sazbaDPHProcent`, `_zk`.`zboziKategorieId`, `_zk`.`zboziId`, `_zk`.`kategorieId`, `_zk`.`zboziKategoriePoradi`, `_k`.`kategorieId`, `_k`.`kategorieNazev`, `_k`.`kategorieCelyNazev`, `_k`.`kategorieKod`, `_k`.`kategorieCesta`, `_k`.`kategoriePopis`, `_k`.`kategorieKeywords`, `_k`.`kategorieRodiceId`, `_k`.`kategoriePoradi`, `_k`.`kategorieSkryta`, `_k`.`kategorieVTopMenu`, `_v`.`vyrobceId`, `_v`.`vyrobceNazev`, `_v`.`vyrobceKod`, `_v`.`vyrobceKoeficient`, `_tzvz`.`typZboziVlastnostZboziId`, `_tzvz`.`typZboziId`, `_tzvz`.`vlastnostZboziId`, `_vzh`.`vlastnostZboziHodnotaId`, `_vzh`.`zboziId`, `_vzh`.`vlastnostZboziId`, `_vzh`.`vlastnostZboziHodnota`, `zvc`.`zboziVyslCenaId` AS`zvc_zboziVyslCenaId`, `zvc`.`zboziVyslCenaZboziId` AS`zvc_zboziVyslCenaZboziId`, `zvc`.`vyslCena` AS`zvc_vyslCena`, `zvc`.`vyslCenaSDPH` AS`zvc_vyslCenaSDPH`, `this`.`zboziId`, `this`.`zboziNazev`, `this`.`zboziKod`, `this`.`zboziIdentifikator`, `this`.`zboziPartNum`, `this`.`zboziEAN`, `this`.`zboziPopis`, `this`.`zboziOstatniParametry`, `this`.`zboziInterniInfo`, `this`.`zboziProdejniCena`, `this`.`zboziAkcniCena`, `this`.`zboziSetovaCena`, `this`.`zboziMocCena`, `this`.`sazbaDPHId`, `this`.`vyrobceId`, `this`.`typZboziId`, `this`.`stavZboziId`, `this`.`skladovaDostupnostId`, `this`.`zdrojCenId`, `this`.`zboziPHE`, `this`.`zboziAutorskyPoplatek`, `this`.`zboziVahovyPoplatek`, `this`.`nemenitStavZbozi` FROM `tbl_Zbozi`AS this LEFT JOIN `reg_SazbaDPH`AS _sd ON this.sazbaDPHId = _sd.sazbaDPHId LEFT JOIN `tbl_Zbozi_Kategorie`AS _zk ON this.zboziId = _zk.zboziId LEFT JOIN `tbl_Kategorie`AS _k ON _zk.kategorieId = _k.kategorieId LEFT JOIN `tbl_Vyrobce`AS _v ON this.vyrobceId = _v.vyrobceId LEFT JOIN `tbl_TypZbozi_VlastnostZbozi`AS _tzvz ON this.typZboziId = _tzvz.typZboziId LEFT JOIN `tbl_VlastnostZboziHodnota`AS _vzh ON this.zboziId = _vzh.zboziId AND _vzh.vlastnostZboziId = _tzvz.vlastnostZboziId LEFT JOIN `tbl_Zbozi_VyslCena`AS zvc ON this.zboziId = zvc.zboziVyslCenaZboziId WHERE _k.kategorieId IN (155317, 5570, 155445, 5706, 5707, 155429, 155430, 155431, 5708, 5709, 5710, 155427, 155426, 155428, 11413, 5713, 5714, 5715, 5716, 5717, 5718, 5719, 5720, 10245, 10253, 11253, 10834, 10269, 10249, 10246, 10247, 10248, 5723, 5725, 5726, 5727, 5728, 5729, 155319, 5815, 5816, 5817, 5818, 5819, 5822, 5824, 5832, 11406, 11411, 11410, 11409, 6069, 6070, 6072, 6073, 6075, 6078, 6086, 11414, 6185, 155433, 6186, 6187, 6188, 6190, 6191, 6193, 6198, 6199, 6200, 6201, 6202, 6203, 6207, 6209, 11442, 6210, 6211, 6212, 6215, 6216, 6217, 6218, 6219, 6220, 155366, 6221, 11339, 11340, 11341, 11359, 6222, 6223, 6224, 6225, 6226, 6227, 6228, 11099, 155376, 6231, 6232, 6233, 6234, 6235, 6236, 155391, 155392, 155437, 6237, 6238, 6241, 6243, 6244, 6245, 6246, 6247, 6248, 6249, 6250, 6251, 6252, 6253, 6254, 6256, 6257, 6258, 6259, 6260, 6261, 10839, 155362, 6262, 6263, 6264, 6265, 155361, 6267, 6269, 11390, 11346, 11112, 11394, 11397, 155393, 6270, 11436, 10292, 6271, 6272, 6275, 6277, 6278, 6279, 6280, 6281, 11348, 10288, 11113, 6283, 6284, 6285, 6287, 155494, 11114, 6292, 6293, 6294, 6295, 6296, 6297, 6298, 6300, 6301, 6302, 6303, 6304, 11116, 6305, 10781, 6306, 6307, 6308, 6309, 6310, 6311, 6313, 6314, 6315, 6316, 6317, 6318, 6327, 6328, 155451, 6333, 6334, 6335, 6337, 6340, 6342, 6343, 6344, 6345, 6346, 11344, 11389, 10289, 10291, 10302, 10303, 10304, 10294, 10306, 10300, 10305, 10293, 10299, 10298, 10290, 10296, 10297, 11454, 11100, 11101, 11117, 131475, 11402, 5680, 5684, 5685, 5686, 5687, 5688, 5689, 11383, 5702, 5703, 5704, 5705) AND stavZboziId IN (2) AND zvc.zboziVyslCenaSkupinaId = '8' ORDER BY _k.kategoriePoradi ASC LIMIT 18
How else could it work? If it applied the order after selecting the 18 records you would get the top 18 records in the default order, which it would then sort. You might get better performance by inserting all the values in your IN statement into a temp table and then joining to the temp table.
it still has to sort 500,000 records to find your 18 so it will be alot slower, you can speed it up by adding indexes to your kategoriePoradi column in your tables