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https://issues.apache.org/jira/browse/IMPALA-7564?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16662783#comment-16662783
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Paul Rogers commented on IMPALA-7564:
-------------------------------------
Expanding on the previous note, suppose we have a star schema: a fact table with
(time-stamp, store-id, sale-id, customer-id, cashier-id, lane-id, payment-type,
total-sale, sales-tax, ...)
We then have dimension tables:
(store-id, location, address, phone, ...)
(cachier-id, name, hire-date, ...)
And so on.
If we optimize such a query, we would normally put the dimension tables on the
build side of a join. You can think of a join to three fact tables as a set of
"enrichment filters", each of which adds more information to the query. (First
look up the store, then the cashier, then the customer, ...)
In each case, it should be clear the primary key in the dimension table: the
column where NDV(col) = |table|.
If the dimension table is small, just use it on the build side. No need to
infer a primary key for the fact table, and the join tells us the FK in the
fact table that points to the (inferred) PK of the dimension table.
The challenge is when, due to cardinality estimates, we try to be clever and
put the fact table on the build side. (Maybe we've decided that filters are so
selective that we'll only get 10 sales, but there are 100s of stores, 100Ks of
customers, etc.) What is the PK of the fact table?
In this case, the PK of the fact table very likely (store-id, lane-id,
timestamp), say, very likely has nothing to do with the dimension table
(customer-id). In this case, we can't expect a join with unique keys: we have
to accept that if we put the fact table on the build side, there will be
duplicate keys (the same customer bought multiple times).
The point is, if we step up a level and understand the data model that the
customer has implemented, we can make better decisions than if we attempt to
reverse engineer that model from the query and metadata. (This is, in fact, why
we use HMS I the first place rather than trying to infer schema directly from
the file as other tools do.)
> Conservative FK/PK join type detection with complex equi-join conjuncts
> -----------------------------------------------------------------------
>
> Key: IMPALA-7564
> URL: https://issues.apache.org/jira/browse/IMPALA-7564
> Project: IMPALA
> Issue Type: Bug
> Components: Frontend
> Affects Versions: Impala 2.12.0, Impala 2.13.0, Impala 3.1.0
> Reporter: bharath v
> Priority: Major
>
> With IMPALA-5547, we predict whether a join is an FK/PK join as follows.
> {noformat}
> // Iterate over all groups of conjuncts that belong to the same joined tuple
> id pair.
> // For each group, we compute the join NDV of the rhs slots and compare
> it to the
> // number of rows in the rhs table.
> for (List<EqJoinConjunctScanSlots> fkPkCandidate:
> scanSlotsByJoinedTids.values()) {
> double jointNdv = 1.0;
> for (EqJoinConjunctScanSlots slots: fkPkCandidate) jointNdv *=
> slots.rhsNdv();
> double rhsNumRows = fkPkCandidate.get(0).rhsNumRows();
> if (jointNdv >= Math.round(rhsNumRows * (1.0 -
> FK_PK_MAX_STATS_DELTA_PERC))) {
> // We cannot disprove that the RHS is a PK.
> if (result == null) result = Lists.newArrayList();
> result.addAll(fkPkCandidate);
> }
> }
> {noformat}
> We iterate through all the "simple" equi join conjuncts on the RHS, multiply
> their NDVs and check if it close to rhsNumRows. The issue here is that this
> can result in conservative FK/Pk detection if the equi-join conjuncts are not
> simple (of the form <slotRef> = <slotRef>)
> {noformat}
> /**
> * Returns a new EqJoinConjunctScanSlots for the given equi-join conjunct
> or null if
> * the given conjunct is not of the form <SlotRef> = <SlotRef> or if the
> underlying
> * table/column of at least one side is missing stats.
> */
> public static EqJoinConjunctScanSlots create(Expr eqJoinConjunct) {
> if (!Expr.IS_EQ_BINARY_PREDICATE.apply(eqJoinConjunct)) return null;
> SlotDescriptor lhsScanSlot =
> eqJoinConjunct.getChild(0).findSrcScanSlot();
> if (lhsScanSlot == null || !hasNumRowsAndNdvStats(lhsScanSlot)) return
> null;
> SlotDescriptor rhsScanSlot =
> eqJoinConjunct.getChild(1).findSrcScanSlot();
> {noformat}
> For example, the following query contains a complex equi-join conjunct
> {{substr(l.c3, 1, 6) = substr(r.c3, 1,6)}}, so while detecting if the left
> outer join is an FK/PK, we just check if
> {{NDVs(r.c1) * NDVs(r.c2) ~ r.numRows()}} which is incorrect. (This happens
> because EqJoinConjunctScanSlots.create() returns null for any non-simple
> predicates which are not considered later).
> {noformat}
> [localhost:21000]> explain select * from test_left l left outer join
> test_right r on l.c1 = r.c1 and l.c2 = r.c2 and substr(l.c3, 1, 6) =
> substr(r.c3, 1,6);
> Query: explain select * from test_left l left outer join test_right r on l.c1
> = r.c1 and l.c2 = r.c2 and substr(l.c3, 1, 6) = substr(r.c3, 1,6)
> +-----------------------------------------------------------------------------------------+
> | Explain String
> |
> +-----------------------------------------------------------------------------------------+
> | Max Per-Host Resource Reservation: Memory=1.95MB Threads=5
> |
> | Per-Host Resource Estimates: Memory=66MB
> |
> |
> |
> | F02:PLAN FRAGMENT [UNPARTITIONED] hosts=1 instances=1
> |
> | | Per-Host Resources: mem-estimate=0B mem-reservation=0B
> thread-reservation=1 |
> | PLAN-ROOT SINK
> |
> | | mem-estimate=0B mem-reservation=0B thread-reservation=0
> |
> | |
> |
> | 04:EXCHANGE [UNPARTITIONED]
> |
> | | mem-estimate=0B mem-reservation=0B thread-reservation=0
> |
> | | tuple-ids=0,1N row-size=94B cardinality=49334767023
> |
> | | in pipelines: 00(GETNEXT)
> |
> | |
> |
> | F00:PLAN FRAGMENT [RANDOM] hosts=1 instances=1
> |
> | Per-Host Resources: mem-estimate=33.94MB mem-reservation=1.95MB
> thread-reservation=2 |
> | 02:HASH JOIN [LEFT OUTER JOIN, BROADCAST]
> |
> | | hash predicates: l.c1 = r.c1, l.c2 = r.c2, substr(l.c3, 1, 6) =
> substr(r.c3, 1, 6) |
> | | fk/pk conjuncts: none
> |
> | | mem-estimate=1.94MB mem-reservation=1.94MB spill-buffer=64.00KB
> thread-reservation=0 |
> | | tuple-ids=0,1N row-size=94B cardinality=49334767023
> |
> | | in pipelines: 00(GETNEXT), 01(OPEN)
> |
> | |
> |
> | |--03:EXCHANGE [BROADCAST]
> |
> | | | mem-estimate=0B mem-reservation=0B thread-reservation=0
> |
> | | | tuple-ids=1 row-size=47B cardinality=2510
> |
> | | | in pipelines: 01(GETNEXT)
> |
> | | |
> |
> | | F01:PLAN FRAGMENT [RANDOM] hosts=1 instances=1
> |
> | | Per-Host Resources: mem-estimate=32.00MB mem-reservation=8.00KB
> thread-reservation=2 |
> | | 01:SCAN HDFS [cdh72724.test_right r, RANDOM]
> |
> | | partitions=1/1 files=1 size=8B
> |
> | | stored statistics:
> |
> | | table: rows=2510 size=8B
> |
> | | columns: all
> |
> | | extrapolated-rows=disabled max-scan-range-rows=2510
> |
> | | mem-estimate=32.00MB mem-reservation=8.00KB thread-reservation=1
> |
> | | tuple-ids=1 row-size=47B cardinality=2510
> |
> | | in pipelines: 01(GETNEXT)
> |
> | |
> |
> | 00:SCAN HDFS [cdh72724.test_left l, RANDOM]
> |
> | partitions=1/1 files=1 size=8B
> |
> | stored statistics:
> |
> | table: rows=589658570 size=8B
> |
> | columns: all
> |
> | extrapolated-rows=disabled max-scan-range-rows=589658570
> |
> | mem-estimate=32.00MB mem-reservation=8.00KB thread-reservation=1
> |
> | tuple-ids=0 row-size=47B cardinality=589658570
> |
> | in pipelines: 00(GETNEXT)
> |
> +-----------------------------------------------------------------------------------------+
> Fetched 48 row(s) in 0.02s
> {noformat}
> We should either consider NDVs of complex conjuncts (error-prone for obvious
> reasons) or generally assume a join to be FK/PK until and unless proven
> otherwise.
> Here is the plan if the complex conjunct is relaxed to a simple <slotRef> =
> <slotRef> type. We can see that it detects the join to be of fk/pk type.
> {noformat}
> [localhost:21000] cdh72724> explain select * from test_left l left outer join
> test_right r on l.c1 = r.c1 and l.c2 = r.c2 and l.c3 = r.c3;
> Query: explain select * from test_left l left outer join test_right r on l.c1
> = r.c1 and l.c2 = r.c2 and l.c3 = r.c3
> +-----------------------------------------------------------------------------------------+
> | Explain String
> |
> +-----------------------------------------------------------------------------------------+
> | Max Per-Host Resource Reservation: Memory=1.95MB Threads=5
> |
> | Per-Host Resource Estimates: Memory=66MB
> |
> |
> |
> | F02:PLAN FRAGMENT [UNPARTITIONED] hosts=1 instances=1
> |
> | | Per-Host Resources: mem-estimate=0B mem-reservation=0B
> thread-reservation=1 |
> | PLAN-ROOT SINK
> |
> | | mem-estimate=0B mem-reservation=0B thread-reservation=0
> |
> | |
> |
> | 04:EXCHANGE [UNPARTITIONED]
> |
> | | mem-estimate=0B mem-reservation=0B thread-reservation=0
> |
> | | tuple-ids=0,1N row-size=94B cardinality=589658570
> |
> | | in pipelines: 00(GETNEXT)
> |
> | |
> |
> | F00:PLAN FRAGMENT [RANDOM] hosts=1 instances=1
> |
> | Per-Host Resources: mem-estimate=33.94MB mem-reservation=1.95MB
> thread-reservation=2 |
> | 02:HASH JOIN [LEFT OUTER JOIN, BROADCAST]
> |
> | | hash predicates: l.c1 = r.c1, l.c2 = r.c2, l.c3 = r.c3
> |
> | | fk/pk conjuncts: l.c1 = r.c1, l.c2 = r.c2, l.c3 = r.c3
> |
> | | mem-estimate=1.94MB mem-reservation=1.94MB spill-buffer=64.00KB
> thread-reservation=0 |
> | | tuple-ids=0,1N row-size=94B cardinality=589658570
> |
> | | in pipelines: 00(GETNEXT), 01(OPEN)
> |
> | |
> |
> | |--03:EXCHANGE [BROADCAST]
> |
> | | | mem-estimate=0B mem-reservation=0B thread-reservation=0
> |
> | | | tuple-ids=1 row-size=47B cardinality=2510
> |
> | | | in pipelines: 01(GETNEXT)
> |
> | | |
> |
> | | F01:PLAN FRAGMENT [RANDOM] hosts=1 instances=1
> |
> | | Per-Host Resources: mem-estimate=32.00MB mem-reservation=8.00KB
> thread-reservation=2 |
> | | 01:SCAN HDFS [cdh72724.test_right r, RANDOM]
> |
> | | partitions=1/1 files=1 size=8B
> |
> | | stored statistics:
> |
> | | table: rows=2510 size=8B
> |
> | | columns: all
> |
> | | extrapolated-rows=disabled max-scan-range-rows=2510
> |
> | | mem-estimate=32.00MB mem-reservation=8.00KB thread-reservation=1
> |
> | | tuple-ids=1 row-size=47B cardinality=2510
> |
> | | in pipelines: 01(GETNEXT)
> |
> | |
> |
> | 00:SCAN HDFS [cdh72724.test_left l, RANDOM]
> |
> | partitions=1/1 files=1 size=8B
> |
> | stored statistics:
> |
> | table: rows=589658570 size=8B
> |
> | columns: all
> |
> | extrapolated-rows=disabled max-scan-range-rows=589658570
> |
> | mem-estimate=32.00MB mem-reservation=8.00KB thread-reservation=1
> |
> | tuple-ids=0 row-size=47B cardinality=589658570
> |
> | in pipelines: 00(GETNEXT)
> |
> +-----------------------------------------------------------------------------------------+
> Fetched 48 row(s) in 0.01s
> {noformat}
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