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Posted to issues@flink.apache.org by "Zongwen Li (Jira)" <ji...@apache.org> on 2022/01/07 02:20:00 UTC
[jira] [Updated] (FLINK-25559) SQL JOIN causes data loss
[ https://issues.apache.org/jira/browse/FLINK-25559?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Zongwen Li updated FLINK-25559:
-------------------------------
Description:
{code:java}
// sql omits some selected fields
INSERT INTO kd_product_info
SELECT
ps.product AS productId,
ps.productsaleid AS productSaleId,
CAST(p.complex AS INT) AS complex,
p.createtime AS createTime,
p.updatetime AS updateTime,
p.ean AS ean,
ts.availablequantity AS totalAvailableStock,
IF
(
ts.availablequantity - ts.lockoccupy - ts.lock_available_quantity > 0,
ts.availablequantity - ts.lockoccupy - ts.lock_available_quantity,
0
) AS sharedStock
,rps.purchase AS purchase
,v.`name` AS vendorName
FROM
product_sale ps
JOIN product p ON ps.product = p.id
LEFT JOIN rate_product_sale rps ON ps.productsaleid = rps.id
LEFT JOIN pss_total_stock ts ON ps.productsaleid = ts.productsale
LEFT JOIN vendor v ON ps.merchant_id = v.merchant_id AND ps.vendor = v.vendor
LEFT JOIN mccategory mc ON ps.merchant_id = mc.merchant_id AND p.mccategory = mc.id
LEFT JOIN new_mccategory nmc ON p.mccategory = nmc.mc
LEFT JOIN product_sale_grade_plus psgp ON ps.productsaleid = psgp.productsale
LEFT JOIN product_sale_extend pse359 ON ps.productsaleid = pse359.product_sale AND pse359.meta = 359
LEFT JOIN product_image_url piu ON ps.product = piu.product {code}
All table sources are upsert-kafka，and format is json;
the data in each table is between 5 million and 10 million, parallelism: 24;
We tested sinking to kudu and ES;
Also tested multiple versions: 1.13.2, 1.13.3, 1.13.5, 1.14.0, 1.14.2;
After many tests, we found that when the left join table is more or the parallelism of the operator is greater, the data will be more easily lost.
was:
{code:java}
// sql omits some selected fields
INSERT INTO kd_product_info
SELECT
ps.product AS productId,
ps.productsaleid AS productSaleId,
CAST(p.complex AS INT) AS complex,
p.createtime AS createTime,
p.updatetime AS updateTime,
p.ean AS ean,
ts.availablequantity AS totalAvailableStock,
IF
(
ts.availablequantity - ts.lockoccupy - ts.lock_available_quantity > 0,
ts.availablequantity - ts.lockoccupy - ts.lock_available_quantity,
0
) AS sharedStock
,rps.purchase AS purchase
,v.`name` AS vendorName
FROM
product_sale ps
JOIN product p ON ps.product = p.id
LEFT JOIN rate_product_sale rps ON ps.productsaleid = rps.id
LEFT JOIN pss_total_stock ts ON ps.productsaleid = ts.productsale
LEFT JOIN vendor v ON ps.merchant_id = v.merchant_id AND ps.vendor = v.vendor
LEFT JOIN mccategory mc ON ps.merchant_id = mc.merchant_id AND p.mccategory = mc.id
LEFT JOIN new_mccategory nmc ON p.mccategory = nmc.mc
LEFT JOIN product_sale_grade_plus psgp ON ps.productsaleid = psgp.productsale
LEFT JOIN product_sale_extend pse359 ON ps.productsaleid = pse359.product_sale AND pse359.meta = 359
LEFT JOIN product_image_url piu ON ps.product = piu.product {code}
All table sources are upsert-kafka，and format is json;
We tested sinking to kudu and ES;
Also tested multiple versions: 1.13.2, 1.13.3, 1.13.5, 1.14.0, 1.14.2;
After many tests, we found that when the left join table is more or the parallelism of the operator is greater, the data will be more easily lost.
> SQL JOIN causes data loss
> -------------------------
>
> Key: FLINK-25559
> URL: https://issues.apache.org/jira/browse/FLINK-25559
> Project: Flink
> Issue Type: Bug
> Components: Table SQL / API
> Affects Versions: 1.14.0, 1.13.2, 1.13.3, 1.13.5, 1.14.2
> Reporter: Zongwen Li
> Priority: Major
>
> {code:java}
> // sql omits some selected fields
> INSERT INTO kd_product_info
> SELECT
> ps.product AS productId,
> ps.productsaleid AS productSaleId,
> CAST(p.complex AS INT) AS complex,
> p.createtime AS createTime,
> p.updatetime AS updateTime,
> p.ean AS ean,
> ts.availablequantity AS totalAvailableStock,
> IF
> (
> ts.availablequantity - ts.lockoccupy - ts.lock_available_quantity > 0,
> ts.availablequantity - ts.lockoccupy - ts.lock_available_quantity,
> 0
> ) AS sharedStock
> ,rps.purchase AS purchase
> ,v.`name` AS vendorName
> FROM
> product_sale ps
> JOIN product p ON ps.product = p.id
> LEFT JOIN rate_product_sale rps ON ps.productsaleid = rps.id
> LEFT JOIN pss_total_stock ts ON ps.productsaleid = ts.productsale
> LEFT JOIN vendor v ON ps.merchant_id = v.merchant_id AND ps.vendor = v.vendor
> LEFT JOIN mccategory mc ON ps.merchant_id = mc.merchant_id AND p.mccategory = mc.id
> LEFT JOIN new_mccategory nmc ON p.mccategory = nmc.mc
> LEFT JOIN product_sale_grade_plus psgp ON ps.productsaleid = psgp.productsale
> LEFT JOIN product_sale_extend pse359 ON ps.productsaleid = pse359.product_sale AND pse359.meta = 359
> LEFT JOIN product_image_url piu ON ps.product = piu.product {code}
> All table sources are upsert-kafka，and format is json;
> the data in each table is between 5 million and 10 million, parallelism: 24;
> We tested sinking to kudu and ES;
> Also tested multiple versions: 1.13.2, 1.13.3, 1.13.5, 1.14.0, 1.14.2;
> After many tests, we found that when the left join table is more or the parallelism of the operator is greater, the data will be more easily lost.
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