Comments (2)
I execute the following sql statement, the server hangs up.
set enable_optimizer = 1; explain pipeline select xxx from xxx as A join xxx as B on A.name = B.name where A.name is not null;The same sql statement will not have any errors when executed on the native clickhouse.
Hi @juppylm thanks for the feedback!
When using optimizer, the query execution model of Byconity is different from CH, so explain pipeline
cannot run.
You can try to explain select xxx from xxx as A join xxx as B on A.name = B.name where A.name is not null;
, but output meaning will also be different from native Clickhouse.
cc @Adora627 have we note this in the doccument?
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For example, explaining an JOIN query will look like this:
EXPLAIN
SELECT
sum(LO_REVENUE),
toYear(LO_ORDERDATE) AS d_year,
P_BRAND
FROM ssb100.lineorder, ssb100.part, ssb100.supplier
WHERE (LO_PARTKEY = P_PARTKEY) AND (LO_SUPPKEY = S_SUPPKEY) AND (P_CATEGORY = 'MFGR#12') AND (S_REGION = 'AMERICA')
GROUP BY
d_year,
P_BRAND
ORDER BY
d_year ASC,
P_BRAND ASC
Query id: 7876f063-a665-40de-9926-6083217455c5
┌─explain───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┐
│ Projection est. 93873 rows, cost 7.398416e+08 │
│ │ Expressions: [P_BRAND], d_year:=`expr#toYear(LO_ORDERDATE)`, sum(LO_REVENUE):=`expr#sum(LO_REVENUE)` │
│ └─ Sorting est. 93873 rows, cost 7.398347e+08 │
│ │ Order by: {expr#toYear(LO_ORDERDATE) asc, P_BRAND asc} │
│ └─ Gather Exchange est. 93873 rows, cost 7.398347e+08 │
│ └─ Sorting est. 93873 rows, cost 7.398197e+08 │
│ │ Order by: {expr#toYear(LO_ORDERDATE) asc, P_BRAND asc} │
│ └─ MergingAggregated est. 93873 rows, cost 7.398197e+08 │
│ └─ Repartition Exchange est. 93873 rows, cost 7.398197e+08 │
│ │ Partition by: {P_BRAND, expr#toYear(LO_ORDERDATE)} │
│ └─ Aggregating est. 93873 rows, cost 7.398046e+08 │
│ │ Group by: {P_BRAND, expr#toYear(LO_ORDERDATE)} │
│ │ Aggregates: expr#sum(LO_REVENUE):=AggNull(sum)(LO_REVENUE) │
│ └─ Projection est. 6742248 rows, cost 7.398046e+08 │
│ │ Expressions: [LO_REVENUE, P_BRAND], expr#toYear(LO_ORDERDATE):=toYear(LO_ORDERDATE) │
│ └─ Inner Join est. 6742248 rows, cost 7.393057e+08 │
│ │ Condition: LO_SUPPKEY == S_SUPPKEY │
│ ├─ Inner Join est. 33634621 rows, cost 7.241307e+08 │
│ │ │ Condition: LO_PARTKEY == P_PARTKEY │
│ │ ├─ Local Exchange est. 600038145 rows, cost 4.884311e+08 │
│ │ │ └─ Filter est. 600038145 rows, cost 4.884311e+08 │
│ │ │ │ Dynamic Filters: {LO_PARTKEY:bloomfilter,LO_PARTKEY:range,LO_SUPPKEY:bloomfilter,LO_SUPPKEY:range} │
│ │ │ └─ TableScan ssb100.lineorder est. 600038145 rows, cost 4.440282e+08 │
│ │ │ Outputs: [LO_ORDERDATE, LO_PARTKEY, LO_REVENUE, LO_SUPPKEY] │
│ │ └─ Broadcast Exchange est. 55736 rows, cost 1.152642e+06 │
│ │ └─ Projection est. 55736 rows, cost 1.143724e+06 │
│ │ │ Expressions: [P_BRAND, P_CATEGORY, P_PARTKEY] │
│ │ │ Dynamic Filters Builder: {P_PARTKEY} │
│ │ └─ Filter est. 55736 rows, cost 1.139600e+06 │
│ │ │ Condition: P_CATEGORY = 'MFGR#12' │
│ │ └─ TableScan ssb100.part est. 1400000 rows, cost 1.036000e+06 │
│ │ Outputs: [P_BRAND, P_CATEGORY, P_PARTKEY] │
│ └─ Broadcast Exchange est. 40125 rows, cost 1.721894e+05 │
│ └─ Projection est. 40125 rows, cost 1.657693e+05 │
│ │ Expressions: [S_REGION, S_SUPPKEY] │
│ │ Dynamic Filters Builder: {S_SUPPKEY} │
│ └─ Filter est. 40125 rows, cost 1.628000e+05 │
│ │ Condition: S_REGION = 'AMERICA' │
│ └─ TableScan ssb100.supplier est. 200000 rows, cost 1.480000e+05 │
│ Outputs: [S_REGION, S_SUPPKEY] │
│ note: Dynamic Filter is applied for 4 times. │
└───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────┘
from byconity.
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