magento 2.0.7 – Some modules use code versions newer or older than the database. First update the module code, then run & # 39; setup: upgrade & # 39;

The code base of the module does not match the DB schema and data.
Magento_Theme scheme: 2.0.1 -> 2.0.0
Magento_Theme data: 2.0.1 -> 2.0.0
Magento client schema: 2.0.9 -> 2.0.6
Magento client data: 2.0.9 -> 2.0.6
Diagram of Magento_Cms: 2.0.1 -> 2.0.0
Data of Magento_Cms: 2.0.1 -> 2.0.0
Magento registration scheme: 2.1.3 -> 2.0.3
Magento catalog data: 2.1.3 -> 2.0.3
Magento_Search scheme: 2.0.4 -> 2.0.1
Magento_Search data: 2.0.4 -> 2.0.1
Schematic of Magento_Quote: 2.0.3 -> 2.0.2
Data of the Magento appointment: 2.0.3 -> 2.0.2
Schema Magento_Msrp: 2.1.3 -> 2.0.0
Magento_Msrp data: 2.1.3 -> 2.0.0
Magento_Bundle scheme: 2.0.2 -> 2.0.1
Magento_Bundle data: 2.0.2 -> 2.0.1
Downloadable Magento schema: 2.0.1 -> 2.0.0
Magento_Downloadable data: 2.0.1 -> 2.0.0
Magento sales scheme: 2.0.3 -> 2.0.1
Magento sales data: 2.0.3 -> 2.0.1
Diagram Magento_CatalogInventory: 2.0.1 -> 2.0.0
Magento_CatalogInventory data: 2.0.1 -> 2.0.0
Schematic of Magento_GroupedProduct: 2.0.1 -> 2.0.0
Magento_GroupedProduct data: 2.0.1 -> 2.0.0
Magento integration scheme: 2.2.0 -> 2.0.1
Magento integration data: 2.2.0 -> 2.0.1
Schema Magento_CatalogRule: 2.0.1 -> 2.0.0
Data of Magento_CatalogRule: 2.0.1 -> 2.0.0
Schema Magento_SalesRule: 2.0.1 -> 2.0.0
Magento_SalesRule data: 2.0.1 -> 2.0.0
Schema Magento_Swatches: 2.0.1 -> 2.0.0
Magento_Swatches data: 2.0.1 -> 2.0.0
Schema Magento_GiftMessage: 2.0.1 -> 2.0.0
Magento_GiftMessage data: 2.0.1 -> 2.0.0
Some modules use code versions that are newer or older than the database. First update the module code, then run & # 39; setup: upgrade & # 39 ;.

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LIVE ~ 78.47.225.59:9050 | 0.275 | Unknown | Unknown | Unknown | Germany | Reviewed in vn5socks.net
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LIVE ~ 195.98.66.138:33256 | 0.338 | Voronezh | 86 | Unknown | Russian Federation | Reviewed in vn5socks.net
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LIVE ~ 185.43.110.132:9999 | 0.344 | Unknown | Unknown | Unknown | Europe | Reviewed in vn5socks.net
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LIVE ~ 119.28.191.18:7070 | 0.046 | Beijing | 22 | Unknown | China | Reviewed in vn5socks.net
LIVE ~ 80.211.94.238:5000 | 0.256 | Unknown | Unknown | Unknown | Denmark | Reviewed in vn5socks.net
LIVE ~ 158.69.243.148:9999 | 0.243 | Lake of the Forest | California | 92630 | U.S | Reviewed in vn5socks.net
LIVE ~ 178.62.228.168:1082 | 0.241 | Unknown | Unknown | Unknown | Russian Federation | Reviewed in vn5socks.net
LIVE ~ 178.62.193.217:3130 | 0.253 | Unknown | Unknown | Unknown | Russian Federation | Reviewed in vn5socks.net
LIVE ~ 188.243.190.110:10000 | 0.28 | Unknown | Unknown | Unknown | Russian Federation | Reviewed in vn5socks.net
LIVE ~ 211.136.100.154:7302 | 0.082 | Carry off | 2. 3 | Unknown | China | Reviewed in vn5socks.net
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LIVE ~ 220.79.34.109:2018 | 0.106 | Seoul | 11 | Unknown | Korea, Republic of | Checked on vn5socks.net
LIVE ~ 18.223.119.11:1081 | 0.239 | Cambridge | MA | 02139 | United States | Checked on vn5socks.net
LIVE ~ 18,191,255.48:1081 | 0.223 | Cambridge | MA | 02139 | United States | Checked on vn5socks.net
LIVE ~ 78.47.225.59:9050 | 0.275 | Unknown | Unknown | Unknown | Germany | Checked on vn5socks.net
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Classification: 5

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Live |

Classification: 5

.

mongodb – Mongo Db Update (upsert) takes several seconds

Specifications of the machine: 12 cores of 64 GB of RAM

Mongo configuration: v4, XFS file system (backed by Flash SAN), 1 set of replicas with 2 replicas, local 10 GB network (latency less than 1 ms)

Operation being carried out: Upsert, the document size is approximately 200 bytes in total Off field _id

Indexes: _ID, {Location: 2dSphere, Title: 1}, TTL

Collection sizes range from 2k – 50k documents.

We are seeing that 80% of the updates are completed in approximately 1 ms, however, we see cases in which they take from 3 to 8 seconds.

During rush hours, we run approximately 4k per second and these jumps are making things difficult.

From what I can say when reading the output below, it is necessary to wait so long to acquire a database lock.
The question is: what can I do to eliminate these long-term updates? If you need more information that you can provide, I hope you have already done enough homework.

A

{
"op": "update",
"ns": "RGC.MyRgcs_42_-73",
"command": {
"q": {
"_id": "3431363530353935333A2D3732373639323633353A53"
}
"or": {
"Rgc": {
"Address": {
"StreetAddress": "Taras Schevchenko Expressway (CT-9)",
"City": "New Britain",
"State": "CT",
"Zip": "06051",
"County": "Hartford",
"Country: United States",
"SPLC": null,
"CountryPostalCodeFilter": 0,
"AbbreviationFormat": 0
}
"Coords": {
"Lat": "41.650595",
"Lon": "-72.769264",
"SpeedLimitOption": null,
"Region": 0
}
"Region": 4,
"Label": "",
"Put your name" : "",
"Time zone": "EST",
"SpeedLimitInfo": {
"Speed": "65",
"SpeedType": "2",
"SpeedTypeString": "Premium",
"LinkIds": [],
"RoadClass": "Interstate",
"Units": "MPH"
}
"Confidence level": "Exactly",
"DistanceFromRoad": 0.0,
"Mistakes": [],
"CrossStreet": null
}
"Location" : {
"type": "point",
"coordinates": [ 
                    -72.7692635, 
                    41.6505953
                ]
            }
"_id": "3431363530353935333A2D3732373639323633353A53",
"Title": 4,
"ExpireAt": ISODate ("2019-01-19T15: 45: 37.982Z")
}
"multi": false,
"upert": true
}
"keysExamined": 0,
"docsExamined": 0,
"nMatched": 0,
"nModified": 0,
"upert": true,
"inserted keys": 3
"numYield": 0,
"locks": {
"Global": {
"AcquireCount": {
"r": NumberLong (1),
"w": NumberLong (1)
}
}
"Database": {
"AcquireCount": {
"w": NumberLong (1)
}
"quireWaitCount": {
"w": NumberLong (1)
}
"timeAcquiringMicros": {
"w": NumberLong (4178085)
}
}
"Collection": {
"AcquireCount": {
"w": NumberLong (1)
}
}
}
"milis": 4181,
"planSummary": "IDHACK",
"execStats": {
"stage": "UPDATE",
"nReturn": 0,
"ecutionTimeMillisEstimate": 0,
"works": 2,
"advanced": 0,
"needTime": 1,
"need performance": 0,
"saveState": 0,
"restoreState": 0,
"isEOF": 1,
"invalid": 0,
"nMatched": 0,
"nWouldModify": 0,
"nInvalidateSkips": 0,
"wouldInsert": true,
"fastmodinsert": false,
"inputStage": {
"stage": "IDHACK",
"nReturn": 0,
"ecutionTimeMillisEstimate": 0,
"works": 1,
"advanced": 0,
"needTime": 0,
"need performance": 0,
"saveState": 0,
"restoreState": 0,
"isEOF": 1,
"invalid": 0,
"keysExamined": 0,
"docsExamined": 0
}
}
"ts": ISODate ("2019-01-19T15: 45: 42.164Z"),
"client": "10.154.18.136",
"all users" : [],
"user": ""
}

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Fire
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[Vn5socks.net] Automatic update 24/7 – Good socks 4h50 PM
LIVE ~ 220.79.34.109:2018 | 0.113 | Seoul | 11 | Unknown | Korea, Republic of | Checked on vn5socks.net
LIVE ~ 110.232.73.134:57238 | 0,119 | Jakarta | 04 | Unknown | Indonesia | Checked on vn5socks.net
LIVE ~ 80.211.94.238:5000 | 0.2 | Unknown | Unknown | Unknown | Denmark | Checked on vn5socks.net
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LIVE ~ 18.223.119.11:1081 | 0.231 | Cambridge | MA | 02139 |

Classification: 5

.

beginner – C ++ Update battery code – Any additional improvements?

The original question can be seen here: Implementation of the stack in C ++ using the linked list

Changes (with Martin's help):

  • Copy of the added constructor and overload of the assignment operator
  • Changed the return type from peek () to const T & instead of T (this avoids unnecessary data copying)
  • The return type of pop () was modified to cancel; now it only removes the top element instead of returning it to the beginning. The user can call peek () and then call pop () to retrieve and then delete the item. This means that we do not have to return T for value, and it also maintains the "Strong Exception Guarantee".
  • Fixed an error in pop () where the new head was removed instead of the previous one
#ifndef TEST_STACK_H
#define TEST_STACK_H

#include 

model 
class stack {

struct node {
T data;
node * previous;

node (data T, node * previous): data (data), previous (previous) {}
};

node * head = nullptr;

int size = 0;
int max = -1; // -1 is isFull () == false when the default constructor is used

public:
stack () = by default;

stack (int max) {
yes (max <= 0) throw std::out_of_range("stack size must be > 0 ");
this-> max = max;
}

// copy constructor

stack (stack const and rhs):
head (copyList (rhs.head)),
size (rhs.size),
max (rhs.size) {}

// assignment operator

stack & operator = (stack const & rhs)
{
tmp stack (rhs);
swap (tmp);

returns * this;
}

~ stack () {
node * n = head;

while (n! = nullptr) {
previous node * n => previous;
delete n;

n = previous;
}
}

void push (const T & object) {
if (isFull ()) throws std :: overflow_error ("can not push to a full stack");

head = new node (object, head);
++ size;
}

const void pop () {
if (head == nullptr) throw std :: underflow_error ("can not get the empty stack item");

node * old = head;
head = head-> previous;

--size;
delete old
}

T peek () {
if (head == nullptr) throw std :: underflow_error ("can not get the empty stack item");
return head-> data;
}

int getSize () {
return size;
}

bool isFull () {
return size == max;
}

bool isEmpty () {
return head == nullptr;
}

void swap (stack & other) noexcept
{
using std :: swap;
swap (head, another head);
swap (size, other size);
swap (max, other.max);
}

private:
node * copyList (node ​​* l)
{
if (l == nullptr) {
returns nullptr;
}
return new node {l-> data, copyList (l-> previous)};
}
};

#determinate if

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Classification: 5

.

Performance: simple update of mysql with 40 million and 128 GB of RAM that takes too long

We are having problems with simple updates in a single table that take a long time. The table contains ~ 40 million rows.

and the job runs every day that truncates the table and inserts new data from other sources in that table.

Here is the table:

CREATE TABLE temp (
NO int (4) NOT NULL AUTO_INCREMENT,
DATE1 date DEFAULT NULL,
CODE int (4) DEFAULT NULL,
TYPE varchar (20) DEFAULT NULL,
SCODE int (4) DEFAULT NULL,
Nature varchar (25) DEFAULT NULL,
UNITS decimals (19,4) DEFAULT NULL,
BNITS decimal (19,4) DEFAULT NULL,
DRECD double DEFAULT & # 39; 0 & # 39 ;,
FNO varchar (50) DEFAULT NULL,
FLAG varchar (5) DEFAULT NULL,
MBAL double DEFAULT NULL,
PBAL double DEFAULT NULL,
MTotalBal double DEFAULT NULL,
PLNOT decimal (19,4) DEFAULT NULL,
Decimal PLBOOK (19,4) DEFAULT NULL,
AGE int (4) DEFAULT NULL,
RETABS decimal (19,4) DEFAULT NULL,
DELAY decimal (19,4) DEFAULT NULL,
INDEX1 decimal (19,4) DEFAULT NULL,
RETINDEXABS decimal (19,4) DEFAULT NULL,
RetIndexCAGR decimal (19,4) DEFAULT NULL,
CURRAMT decimal (19,4) DEFAULT NULL,
GLOSSLT decimal (19,4) DEFAULT NULL,
GLOSSST decimal (19,4) DEFAULT NULL,
UNITSFORDIVID decimal (19,4) DEFAULT NULL,
double factor DEFAULT NULL,
LNav double DEFAULT & # 39; 10 & # 39 ;,
Date2 date DEFAULT NULL,
IType int (4) DEFAULT NULL,
Double rate DEFAULT NULL,
CurrAmt double DEFAULT NULL,
IndexVal double DEFAULT NULL,
LatestIndexVal double DEFAULT NULL,
Field int (4) DEFAULT NULL,
C_Code int (4) DEFAULT NULL,
B_Code int (4) DEFAULT NULL,
Rm_Code int (4) DEFAULT NULL,
Group_name varchar (100) DEFAULT NULL,
Type 1 varchar (20) DEFAULT NULL,
Type2 varchar (20) DEFAULT NULL,
IsOnline tinyint (3) unsigned DEFAULT NULL,
SFactor double DEFAULT NULL,
OS_Code int (4) DEFAULT NULL,
PRIMARY KEY (NO)
SCODE KEY (SCODE),
KEY C_Code (C_Code),
TYPE OF KEY (TYPE),
KEY OS_Code (OS_Code),
KEY LNav (LNav),
KEY IDX_1 (AGE, Type 2),
KEY DATE1 (DATE1)
) MOTOR = InnoDB DEFAULT CHARSET = utf8mb4 COLLATE = utf8mb4_0900_ai_ci

note: the reason for having so many indexes is that we have many selections in the future that will decrease the explorations of the table.

UPDATE Temp
INNER JOIN SchDate ON Temp.Sch_Code = SchDate.Sch_Code
SET LatestNav = NavRs, NavDate = LDate;
- The SchDate table contains 41K record

UPDATE Temp
SET Age = DATEDIFF (NAVDATE, TR_DATE),
CurrAmt = (LatestNav * Units),
PL_Notional = (UNITS * (LatestNav - Rate)),
Divd_Recd = 0;
Here is my.cnf for reference

[client]
port = 3307
max_execution_time = 0
local_infile = 1

[mysql]
no beep

[mysqld]

port = 3307
# jump blocking
# skip-name-resolution
default_authentication_plugin = mysql_native_password
wait_timeout = 300
interactive_timeout = 300
default-storage-engine = INNODB
sql-mode = "NO_ENGINE_SUBSTITUTION, ANSI_QUOTES"
max_execution_time = 0
innodb_autoinc_lock_mode = 0
group_concat_max_len = 153600
skip-log-bin
log_bin_trust_function_creators = 1
#expire_logs_days = 3
local_infile = 1
skip-log-bin


### Parameters related to cache / buffer ###
table_open_cache = 1024000
open_files_limit = 2048000
key_buffer_size = 2147483648

# myisam_max_sort_file_size = 1G
# myisam_sort_buffer_size = 512M
# myisam_repair_threads = 1



# General and slow registration.
log-output = ARCHIVE
# general-log = 0
# general_log_file = "E:  Mysql  MySQL Server 8.0  Data  2016SERVER.log"
# slow-query-log = 1
# slow_query_log_file = "E:  Mysql  MySQL Server 8.0  Data  2016SERVER-slow.log"
long_query_time = 100


# Specific values ​​of the thread
sort_buffer_size = 2147483648
read_buffer_size = 2147483648
read_rnd_buffer_size = 1073741824
join_buffer_size = 1073741824
thread_cache_size = 600
bulk_insert_buffer_size = 4294967296

### Mysql Directory & Tables ###
datadir = "E:  Mysql  Data  Data "
tmp_table_size = 17179869184

max_heap_table_size = 8589934592



### Parameters related to Innodb ###
# innodb_force_recovery = 3

## Innodb start-stop related parameter
innodb_max_dirty_pages_pct = 0
innodb_buffer_pool_dump_pct = 100
innodb_buffer_pool_dump_at_shutdown = 1
innodb_buffer_pool_load_at_startup = 1

innodb_change_buffer_max_size = 50
innodb_file_per_table = 1
innodb_log_file_size = 10G
innodb_log_buffer_size = 4294967295
innodb_log_files_in_group = 10
#innodb_buffer_pool_chunk_size = 1024M
innodb_buffer_pool_size = 96636764160
### innodb_buffer_pool_size = 90G
innodb_buffer_pool_instances = 50
# innodb_flush_method = O_DIRECT
innodb_flush_log_at_trx_commit = 1
innodb_lock_wait_timeout = 100
innodb_write_io_threads = 64
innodb_read_io_threads = 64

# Binary Logging.
# log-bin = "E:  Mysql  Data  Data  2016SERVER-bin"

# Registration error.
log-error = "E:  Mysql  Data  Data  2016SERVER.err"

# Id. From the server.
Server ID = 2

lower_case_table_names = 1

# Secure File Priv.
secure-file-priv = "E:  Mysql  Uploads"
max_connections = 500
# innodb_thread_concurrency = 9

innodb_thread_concurrency = 0
innodb_adaptive_max_sleep_delay = 150000
innodb_autoextend_increment = 2048
# innodb_concurrency_tickets = 5000
# innodb_old_blocks_time = 1000
innodb_open_files = 1500
innodb_stats_on_metadata = 0
innodb_checksum_algorithm = 0
# back_log = 80
# flush_time = 0
max_allowed_packet = 512M
table_definition_cache = 1400
binlog_row_event_max_size = 8K
# sync_master_info = 10000
# sync_relay_log = 10000
# sync_relay_log_info = 10000
loose_mysqlx_port = 33060

innodb_flush_method = without buffer
### innodb_flush_method = async_unbuffered
default-time-zone = +05: 30
tmpdir = "C: / TEMP"
innodb_io_capacity = 1000
plugin_dir = "C: / Program Files / MySQL / MySQL Server 8 / lib / plugin"
innodb_log_write_ahead_size = 16394
mysqlx_max_connections = 500
innodb_random_read_ahead = 1

the first update takes 30 to 35 minutes and the second update takes 15 minutes.

Here is the explanatory plan for update 1.

1 SIMPLE SchDate index PRIMARY, Sch_Code, IDX_1 Sch_Code 4 39064 100 Use of index
1 SIMPLE temp ref. SCH_Code SCH_Code 9 SchDate.Sch_Code 1 100 Using the index condition

I am running this query in Windows 10. Is there any way to increase the speed of the UPDATE query? Any changes related to the configuration would be useful?

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Classification: 5

.