CPU Usage go over 90%

Hi team,

When using your woodmart theme my server CPU usage going above 90%… and when i change theme with any other ecommerce theme then its stable with 15-20%… What will be root cause of this? Can you please with this?

Hello,

Thank you so much for contacting our support center.

To better assist you, could you kindly test the functionality with default WordPress themes such as TwentyTwenty or WooCommerce Storefront? This will help us determine whether the issue stems from our theme or elsewhere.

Regards

[dev-9059]

Yes we tested with wordpress free theme like OceanWp theme and storefront too… and with these two CPU usage showing 20% only max… but when i revert with Woodmart theme then this goes to above 90%…

Is your woodmart theme is optimized with woocommerce or not?

• This reply was modified 1 day, 4 hours ago by dev-9059.

Hello,

Could you please record a video of how we can reproduce the issue on your website? We need to see how you test it both with WoodMart and WooCommerce Storefront (default theme).

Thank you in advance.

Please check Videos:
Woodmart: https://www.loom.com/share/c74b5bea11ca4d1e9ee697a61bdb3c1b?sid=e22163c4-c81d-4a71-b2e1-525804e25c55

Without Woodmart: https://www.loom.com/share/7ff1cdc46949491bbf001499c194b468?sid=942a1af9-ebb2-402b-a499-28c40b765f10

One more thing i need to share with you… I get support from godaddy server and they give me a script which is running multiple time in backend pleas check below:

SELECT min( min_price ) as min_price, MAX( max_price ) as max_price
FROM zh9q_wc_product_meta_lookup
WHERE product_id IN (
SELECT ID FROM zh9q_posts
LEFT JOIN zh9q_term_relationships ON (zh9q_posts.ID = zh9q_term_relationships.object_id) LEFT JOIN zh9q_term_relationships AS tt1 ON (zh9q_posts.ID = tt1.object_id) LEFT JOIN zh9q_term_relationships AS tt2 ON (zh9q_posts.ID = tt2.object_id) LEFT JOIN zh9q_term_relationships AS tt3 ON (zh9q_posts.ID = tt3.object_id) LEFT JOIN zh9q_term_relationships AS tt4 ON (zh9q_posts.ID = tt4.object_id) LEFT JOIN zh9q_term_relationships AS tt5 ON (zh9q_posts.ID = tt5.object_id) LEFT JOIN zh9q_term_relationships AS tt6 ON (zh9q_posts.ID = tt6.object_id) LEFT JOIN zh9q_term_relationships AS tt7 ON (zh9q_posts.ID = tt7.object_id) LEFT JOIN zh9q_term_relationships AS tt8 ON (zh9q_posts.ID = tt8.object_id) LEFT JOIN zh9q_term_relationships AS tt9 ON (zh9q_posts.ID = tt9.object_id) LEFT JOIN zh9q_term_relationships AS tt10 ON (zh9q_posts.ID = tt10.object_id) LEFT JOIN zh9q_term_relationships AS tt11 ON (zh9q_posts.ID = tt11.object_id) LEFT JOIN zh9q_term_relationships AS tt12 ON (zh9q_posts.ID = tt12.object_id) LEFT JOIN zh9q_term_relationships AS tt13 ON (zh9q_posts.ID = tt13.object_id) LEFT JOIN zh9q_term_relationships AS tt14 ON (zh9q_posts.ID = tt14.object_id)
WHERE zh9q_posts.post_type IN (‘product’)
AND zh9q_posts.post_status = ‘publish’
AND (
(
zh9q_posts.ID NOT IN (
SELECT object_id
FROM zh9q_term_relationships
WHERE term_taxonomy_id IN (7)
)
AND
zh9q_term_relationships.term_taxonomy_id IN (411,436,437,439,440,441,455,759,789)
)
AND
(
(
tt1.term_taxonomy_id IN (405,406,407,408,410,411,412,413,414,415,417,418,419,420,421,422,423,424,425,426,427,428,429,430,431,433,434,435,436,437,439,440,441,483,493,495,777,780)
AND
(
tt2.term_taxonomy_id IN (436,437,439,440,441)
)
)
OR
(
tt3.term_taxonomy_id IN (454,455,456,457,757,758,759)
AND
(
tt4.term_taxonomy_id IN (455,759)
)
)
OR
(
tt5.term_taxonomy_id IN (462,785,786,787,788,789)
AND
(
tt6.term_taxonomy_id IN (789)
)
)
)
AND
(
(
zh9q_posts.ID NOT IN (
SELECT object_id
FROM zh9q_term_relationships
WHERE term_taxonomy_id IN (7)
)
AND
tt7.term_taxonomy_id IN (411,436,437,439,440,441,455,759,789)
)
AND
(
(
tt8.term_taxonomy_id IN (405,406,407,408,410,411,412,413,414,415,417,418,419,420,421,422,423,424,425,426,427,428,429,430,431,433,434,435,436,437,439,440,441,483,493,495,777,780)
AND
(
tt9.term_taxonomy_id IN (436,437,439,440,441)
)
)
OR
(
tt10.term_taxonomy_id IN (454,455,456,457,757,758,759)
AND
(
tt11.term_taxonomy_id IN (455,759)
)
)
OR
(
tt12.term_taxonomy_id IN (462,785,786,787,788,789)
AND
(
tt13.term_taxonomy_id IN (789)
)
)
)
AND
tt14.term_taxonomy_id IN (713)
)
)
)

And check this also:

Using MySQL’s EXPLAIN FORMAT=JSON statement on the query shows a very high ‘query cost’ due to the subquery being generated as a result of the the nested JOINs: “query_cost”: “40176098982.46”. It also highlights how much data is being joined in succession across these subqueries. Below are the estimated values leading up the final join:

“rows_produced_per_join”: 20686423,
“data_read_per_join”: “473M”
“rows_produced_per_join”: 197792185,
“data_read_per_join”: “4G”
“rows_produced_per_join”: 1891179904,
“data_read_per_join”: “42G”
“rows_produced_per_join”: 18082420304,
“data_read_per_join”: “404G”
“rows_produced_per_join”: 172894130155,
“data_read_per_join”: “3T”

Your theme takes the data read to 3TB… that why server getting down.

[Author]

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