The following practices are recommended when running queries:
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If a query fails to offload and you cannot identify the reason, enable tracing and query the
INFORMATION_SCHEMA.OPTIMIZER_TRACE
table to debug the query. See Section 2.3.6, “Debugging Queries”.If the optimizer trace does not return all of the trace information, increase the optimizer trace buffer size. The
MISSING_BYTES_BEYOND_MAX_MEM_SIZE
column of theINFORMATION_SCHEMA.OPTIMIZER_TRACE
table shows how many bytes are missing from a trace. If the column shows a non-zero value, increase theoptimizer_trace_max_mem_size
setting accordingly. For example:SET optimizer_trace_max_mem_size=1000000;
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If an
INFORMATION_SCHEMA.OPTIMIZER_TRACE
query trace indicates that a subquery is not yet supported, try unnesting the subquery. For example, the following query contains a subquery and is not offloaded as indicated by theEXPLAIN
output, which does not show “Using secondary engine”.mysql> EXPLAIN SELECT COUNT(*) FROM orders o WHERE o_totalprice> (SELECT AVG(o_totalprice) FROM orders WHERE o_custkey=o.o_custkey); *************************** 1. row *************************** id: 1 select_type: PRIMARY table: o partitions: NULL type: ALL possible_keys: NULL key: NULL key_len: NULL ref: NULL rows: 14862970 filtered: 100.00 Extra: Using where *************************** 2. row *************************** id: 2 select_type: DEPENDENT SUBQUERY table: orders partitions: NULL type: ALL possible_keys: NULL key: NULL key_len: NULL ref: NULL rows: 14862970 filtered: 10.00 Extra: Using where 2 rows in set, 2 warnings (0.00 sec)
This query can be rewritten as follows to unnest the subquery so that it can be offloaded.
mysql> EXPLAIN SELECT COUNT(*) FROM orders o, (SELECT o_custkey, AVG(o_totalprice) a_totalprice FROM orders GROUP BY o_custkey)a WHERE o.o_custkey=a.o_custkey AND o.o_totalprice>a.a_totalprice;
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By default,
SELECT
queries are offloaded to HeatWave for execution and fall back to the MySQL DB System if that is not possible. To force a query to execute on HeatWave or fail if that is not possible, set theuse_secondary_engine variable
toFORCED
. In this mode, aSELECT
statement returns an error if it cannot be offloaded. Theuse_secondary_engine
variable can be set as shown: -
If you encounter out-of-memory errors when running queries:
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Avoid or rewrite queries that produce a Cartesian product. In the following query, a
JOIN
predicated is not defined between thesupplier
andnation
tables, which causes the query to select all rows from both tables:mysql> SELECT s_nationkey, s_suppkey, l_comment FROM lineitem, supplier, nation WHERE s_suppkey = l_suppkey LIMIT 10; ERROR 3015 (HY000): Out of memory in storage engine 'Failure detected in RAPID; query execution cannot proceed'.
To avoid the Cartesian product, add a relevant predicate between the
supplier
andnation
tables to filter out rows:mysql> SELECT s_nationkey, s_suppkey, l_comment FROM lineitem, supplier, nation WHERE s_nationkey = n_nationkey AND s_suppkey = l_suppkey LIMIT 10;
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Avoid or rewrite queries that produce a Cartesian product introduced by the MySQL optimizer. Due to lack of quality statistics or non-optimal cost decisions, MySQL optimizer may introduce one or more Cartesian products in a query even if a query has predicates defined among all participating tables. For example:
mysql> SELECT o_orderkey, c_custkey, l_shipdate, s_nationkey, s_suppkey, l_comment FROM lineitem, supplier, nation, customer, orders WHERE c_custkey = o_custkey AND o_orderkey = l_orderkey AND c_nationkey = s_nationkey AND c_nationkey = n_nationkey AND c_custkey < 3000000 LIMIT 10; ERROR 3015 (HY000): Out of memory in storage engine 'Failure detected in RAPID; query execution cannot proceed'.
The
EXPLAIN
plan output shows that there is no common predicate between the first two table entries (NATION
andSUPPLIER
).mysql> EXPLAIN SELECT o_orderkey, c_custkey, l_shipdate, s_nationkey, s_suppkey, l_comment FROM lineitem, supplier, nation, customer, orders WHERE c_custkey = o_custkey AND o_orderkey = l_orderkey AND c_nationkey = s_nationkey AND c_nationkey = n_nationkey AND c_custkey < 3000000 LIMIT 10; *************************** 1. row *************************** id: 1 select_type: SIMPLE table: supplier partitions: NULL type: ALL possible_keys: NULL key: NULL key_len: NULL ref: NULL rows: 99626 filtered: 100.00 Extra: Using secondary engine RAPID *************************** 2. row *************************** id: 1 select_type: SIMPLE table: nation partitions: NULL type: ALL possible_keys: NULL key: NULL key_len: NULL ref: NULL rows: 25 filtered: 10.00 Extra: Using where; Using join buffer (hash join); Using secondary engine RAPID *************************** 3. row *************************** id: 1 select_type: SIMPLE table: customer partitions: NULL type: ALL possible_keys: NULL key: NULL key_len: NULL ref: NULL rows: 1382274 filtered: 5.00 Extra: Using where; Using join buffer (hash join); Using secondary engine RAPID *************************** 4. row *************************** id: 1 select_type: SIMPLE table: orders partitions: NULL type: ALL possible_keys: NULL key: NULL key_len: NULL ref: NULL rows: 14862970 filtered: 10.00 Extra: Using where; Using join buffer (hash join); Using secondary engine RAPID *************************** 5. row *************************** id: 1 select_type: SIMPLE table: lineitem partitions: NULL type: ALL possible_keys: NULL key: NULL key_len: NULL ref: NULL rows: 56834662 filtered: 10.00 Extra: Using where; Using join buffer (hash join); Using secondary engine RAPID
To force a join order so that there are predicates associated with each pair of tables, add a
STRAIGHT_JOIN
hint. For example:mysql> EXPLAIN SELECT o_orderkey, c_custkey, l_shipdate, s_nationkey, s_suppkey, l_comment FROM SUPPLIER STRAIGHT_JOIN CUSTOMER STRAIGHT_JOIN NATION STRAIGHT_JOIN ORDERS STRAIGHT_JOIN LINEITEM WHERE c_custkey = o_custkey and o_orderkey = l_orderkey AND c_nationkey = s_nationkey AND c_nationkey = n_nationkey AND c_custkey < 3000000 LIMIT 10; *************************** 1. row *************************** id: 1 select_type: SIMPLE table: supplier partitions: NULL type: ALL possible_keys: NULL key: NULL key_len: NULL ref: NULL rows: 99626 filtered: 100.00 Extra: Using secondary engine RAPID *************************** 2. row *************************** id: 1 select_type: SIMPLE table: customer partitions: NULL type: ALL possible_keys: NULL key: NULL key_len: NULL ref: NULL rows: 1382274 filtered: 5.00 Extra: Using where; Using join buffer (hash join); Using secondary engine RAPID *************************** 3. row *************************** id: 1 select_type: SIMPLE table: nation partitions: NULL type: ALL possible_keys: NULL key: NULL key_len: NULL ref: NULL rows: 25 filtered: 10.00 Extra: Using where; Using join buffer (hash join); Using secondary engine RAPID *************************** 4. row *************************** id: 1 select_type: SIMPLE table: orders partitions: NULL type: ALL possible_keys: NULL key: NULL key_len: NULL ref: NULL rows: 14862970 filtered: 10.00 Extra: Using where; Using join buffer (hash join); Using secondary engine RAPID *************************** 5. row *************************** id: 1 select_type: SIMPLE table: lineitem partitions: NULL type: ALL possible_keys: NULL key: NULL key_len: NULL ref: NULL rows: 56834662 filtered: 10.00 Extra: Using where; Using join buffer (hash join); Using secondary engine RAPID
Avoid or rewrite queries that produce a very large result set. This is a common cause of out of memory errors during query processing. Use aggregation functions, a
GROUP BY
clause, or aLIMIT
clause to reduce the result set size.Avoid or rewrite queries that produce a very large intermediate result set. In certain cases, large result sets can be avoided by adding a
STRAIGHT_JOIN
hint, which enforces a join order in a decreasing of selectiveness.-
Check the size of your data by performing a cluster size estimate. If your data has grown substantially, the HeatWave Cluster may require additional nodes.
For HeatWave on OCI, see Generating a Node Count Estimate in the HeatWave on OCI Service Guide.
For HeatWave on AWS, see Estimating Cluster Size with HeatWave Autopilot in the HeatWave on AWS Service Guide.
For HeatWave for Azure, see Provisioning HeatWave Nodes in the HeatWave for Azure Service Guide.
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HeatWave optimizes for network usage by default. Try running the query with the
MIN_MEM_CONSUMPTION
strategy by setting by settingrapid_execution_strategy
toMIN_MEM_CONSUMPTION
. Therapid_execution_strategy
variable can be set as shown:-
Using a
SET
statement before running queries:mysql> SET SESSION rapid_execution_strategy = MIN_MEM_CONSUMPTION;
-
Using a
SET_VAR
optimizer hint when issuing a query:mysql> SELECT /*+ SET_VAR(rapid_execution_strategy = MIN_MEM_CONSUMPTION) */ ... FROM ...
Unloading tables that are not used. These tables consume memory on HeatWave nodes unnecessarily. See Section 2.5.1, “Unloading Tables”.
Excluding table columns that are not accessed by your queries. These columns consume memory on HeatWave nodes unnecessarily. This strategy requires reloading data. See Section 2.2.2.1, “Excluding Table Columns”.
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After running queries, consider using HeatWave Autopilot Advisor for encoding and data placement recommendations. See Section 2.7, “Workload Optimization for OLAP”.
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