We are running some tests to check the in-memory performance on a 12c (12.1.0.2.4 EE) RAC. Servers have 56GB memory and 20core CPUs.
Our plan is to have a few read-performance critical tables in memory and the rest in disk. The test was to first populate the tables using our insert tool and then run queries on it using JMeter (web application benchmark tool).
The insert tool basically reads records from a file and then inserts records to the DB in blocks and commits.
We started testing with one table and observed slow insert rates straightaway. But when the table is made a no inmemory table the insert rates were fine.
The table has 90 columns, 1 trigger, 15 indexes.
The test preparation and results are given below.
Preparation
1) Create the table, trigger, indexes.
2) Make table in-memory using "alter table test_table inmemory priority critical"
Results
Without Inmemory option (~7000 recs/sec)
Avg time to read 1 record = [0.0241493] ms
Avg time to insert 1 record = [0.141788] ms
Avg time to insert 1 block of 500 number of rows = [70.894] ms
Avg time to commit 2 blocks(500 rows per block) = [3.888] ms
Total time for 2000 blocks of inserts = [141.788] s, at [7052.78] recs/s
Total time for 1000 number of commits = [3.888] s
Total time for 2000 blocks of inserts + 1000 number of commits = [145.676] s
Total time to read 1000000 number of records from file = [24.1493] s
Total time to read 1000000 number of records + 2000 blocks of inserts + 1000 number of commits = [169.825] s
With Inmemory option (~200 recs/sec)
Avg time to read 1 record = [0.0251651] ms
Avg time to insert 1 record = [4.62541] ms
Avg time to insert 1 block of 500 number of rows = [2312.7] ms
Avg time to commit 2 blocks(500 rows per block) = [3.32] ms
Total time for 200 blocks of inserts = [462.541] s, at [216.197] recs/s
Total time for 100 number of commits = [0.332] s
Total time for 200 blocks of inserts + 100 number of commits = [462.873] s
Total time to read 100000 number of records from file = [2.51651] s
Total time to read 100000 number of records + 200 blocks of inserts + 100 number of commits = [465.39] s
The memory parameters of the DB are given below.
NAME TYPE VALUE
lock_sga boolean FALSE
pre_page_sga boolean TRUE
sga_max_size big integer 30G
sga_target big integer 30G
unified_audit_sga_queue_size integer 1048576
inmemory_clause_default string
inmemory_force string DEFAULT
inmemory_max_populate_servers integer 8
inmemory_query string ENABLE
inmemory_size big integer 10G
inmemory_trickle_repopulate_ integer 1
servers_percent
optimizer_inmemory_aware boolean TRUE
buffer_pool_keep string
buffer_pool_recycle string
db_block_buffers integer 0
log_buffer big integer 1048552K
use_indirect_data_buffers boolean FALSE
memory_max_target big integer 0
memory_target big integer 0
optimizer_inmemory_aware boolean TRUE
pga_aggregate_limit big integer 8G
pga_aggregate_target big integer 4G
We are also tried the following, but the results were the same.
1) Stop one instance on the RAC (2 node RAC)
2) Change the inmemory priority to "high" then "low".
Hope someone can point me in the right direction.
Best Answer
The DML in Inmemory involves new features like Journal & Inmemory Transaction Manager. When there is an insert operation on a table enabled for Inmemory, these new features get updated to bring the consistency in Transaction. Sometimes, there are overheads involved in keeping Inmemory Column Unit (IMCU) transactionally consistent.
Following are some of the factors which affect the performance:
For example: Tables with higher compression levels will incur more overhead than tables with lower compression levels.
Following are few other deciding factors which can be fine-tuned:
So, all these combined decide the runtime for an insert. Also, do look at the bundle path updates which are targeted for OLTP & DW performance improvements.
To improve performance in your case you can try changing the compression level used for the table to
memcompress for dml
:alter table test_table inmemory priority critical memcompress for dml duplicate all
Regarding the methods you had tried:
Stopping one instance doesn't affect the performance as RAC nodes are mainly used for Inmemory Fault Tolerance through the DUPLICATE/DISTRIBUTE clause used for the inmeomory table. So, it won't help improve the insert performance.
Changing the priority clause is mainly used while populating/repopulating the table into inmemory. When there are many tables enabled for inmemory, the IMCO picks up the tables based on the priority setting (
CRITICAL, HIGH, MEDIUM, LOW & NONE
) and loads them into inmemory area. So, keeping the table priority to high or more has an impact when the expectation is to immediately see the updated version of table after an insert. For this, the IMCO duration needs to be fine-tuned.