We have MySQL 5.7 master - slaves replications and on the slave servers side, it hapens from time to time that our application monitoring tools (Tideways and PHP7.0) are reporting
MySQL has gone away.
Checking the MYSQL side:
show global status like '%Connection%';
+-----------------------------------+----------+
| Variable_name | Value |
+-----------------------------------+----------+
| Connection_errors_accept | 0 |
| Connection_errors_internal | 0 |
| Connection_errors_max_connections | 0 |
| Connection_errors_peer_address | 323 |
| Connection_errors_select | 0 |
| Connection_errors_tcpwrap | 0 |
| Connections | 55210496 |
| Max_used_connections | 387 |
| Slave_connections | 0 |
+-----------------------------------+----------+
The Connection_errors_peer_address shows 323. How to further investigate on what is causing this issue on both sides:
MySQL has gone away
and
Connection_errors_peer_address
EDIT:
Master Server
net_retry_count = 10
net_read_timeout = 120
net_write_timeout = 120
skip_networking = OFF
Aborted_clients = 151650
Slave Server 1
net_retry_count = 10
net_read_timeout = 30
net_write_timeout = 60
skip_networking = OFF
Aborted_clients = 3
Slave Server 2
net_retry_count = 10
net_read_timeout = 30
net_write_timeout = 60
skip_networking = OFF
Aborted_clients = 3
In MySQL 5.7, when a new TCP/IP connection reaches the server, the server performs several checks, implemented in sql/sql_connect.cc in function check_connection()
One of these checks is to get the IP address of the client side connection, as in:
static int check_connection(THD *thd)
{
...
if (!thd->m_main_security_ctx.host().length) // If TCP/IP connection
{
...
peer_rc= vio_peer_addr(net->vio, ip, &thd->peer_port, NI_MAXHOST);
if (peer_rc)
{
/*
Since we can not even get the peer IP address,
there is nothing to show in the host_cache,
so increment the global status variable for peer address errors.
*/
connection_errors_peer_addr++;
my_error(ER_BAD_HOST_ERROR, MYF(0));
return 1;
}
...
}
Upon failure, the status variable connection_errors_peer_addr is incremented, and the connection is rejected.
vio_peer_addr() is implemented in vio/viosocket.c (code simplified to show only the important calls)
my_bool vio_peer_addr(Vio *vio, char *ip_buffer, uint16 *port,
size_t ip_buffer_size)
{
if (vio->localhost)
{
...
}
else
{
/* Get sockaddr by socked fd. */
err_code= mysql_socket_getpeername(vio->mysql_socket, addr, &addr_length);
if (err_code)
{
DBUG_PRINT("exit", ("getpeername() gave error: %d", socket_errno));
DBUG_RETURN(TRUE);
}
/* Normalize IP address. */
vio_get_normalized_ip(addr, addr_length,
(struct sockaddr *) &vio->remote, &vio->addrLen);
/* Get IP address & port number. */
err_code= vio_getnameinfo((struct sockaddr *) &vio->remote,
ip_buffer, ip_buffer_size,
port_buffer, NI_MAXSERV,
NI_NUMERICHOST | NI_NUMERICSERV);
if (err_code)
{
DBUG_PRINT("exit", ("getnameinfo() gave error: %s",
gai_strerror(err_code)));
DBUG_RETURN(TRUE);
}
...
}
...
}
In short, the only failure path in vio_peer_addr() happens when a call to mysql_socket_getpeername() or vio_getnameinfo() fails.
mysql_socket_getpeername() is just a wrapper on top of getpeername().
The man 2 getpeername manual lists the following possible errors:
NAME
getpeername - get name of connected peer socket
ERRORS
EBADF The argument sockfd is not a valid descriptor.
EFAULT The addr argument points to memory not in a valid part of the process address space.
EINVAL addrlen is invalid (e.g., is negative).
ENOBUFS
Insufficient resources were available in the system to perform the operation.
ENOTCONN
The socket is not connected.
ENOTSOCK
The argument sockfd is a file, not a socket.
Of these errors, only ENOBUFS is plausible.
As for vio_getnameinfo(), it is just a wrapper on getnameinfo(), which also according to the man page man 3 getnameinfo can fail for the following reasons:
NAME
getnameinfo - address-to-name translation in protocol-independent manner
RETURN VALUE
EAI_AGAIN
The name could not be resolved at this time. Try again later.
EAI_BADFLAGS
The flags argument has an invalid value.
EAI_FAIL
A nonrecoverable error occurred.
EAI_FAMILY
The address family was not recognized, or the address length was invalid for the specified family.
EAI_MEMORY
Out of memory.
EAI_NONAME
The name does not resolve for the supplied arguments. NI_NAMEREQD is set and the host's name cannot be located, or neither
hostname nor service name
were requested.
EAI_OVERFLOW
The buffer pointed to by host or serv was too small.
EAI_SYSTEM
A system error occurred. The error code can be found in errno.
The gai_strerror(3) function translates these error codes to a human readable string, suitable for error reporting.
Here many failures can happen, basically due to heavy load or the network.
To understand the process behind this code, what the MySQL server is essentially doing is a Reverse DNS lookup, to:
find the hostname of the client
find the IP address corresponding to this hostname
to later convert this IP address to a hostname again (see the call to ip_to_hostname() that follows).
Overall, failures accounted with Connection_errors_peer_address can be due to system load (causing transient failures like out of memory, etc) or due to network issues affecting DNS.
Disclosure: I happen to be the person who implemented this Connection_errors_peer_address status variable in MySQL, as part of an effort to have better visibility / observability in this area of the code.
[Edit] To follow up with more details and/or guidelines:
When Connection_errors_peer_address is incremented, the root cause is not printed in logs. That is unfortunate for troubleshooting, but also avoid flooding logs causing even more damage, there is a tradeoff here. Keep in mind that anything that happen before logging in is very sensitive ...
If the server really goes out of memory, it is very likely that many other things will break, and that the server will go down very quickly. By monitoring the total memory usage of mysqld, and monitoring the uptime, it should be fairly easy to determine if the failure "only" caused connections to be closed with the server staying up, or if the server itself failed catastrophically.
Assuming the server stays up on failure, the more likely culprit is the second call then, to getnameinfo.
Using skip-name-resolve will have no effect, as this check happens later (see specialflag & SPECIAL_NO_RESOLVE in the code in check_connection())
When Connection_errors_peer_address fails, note that the server cleanly returns the error ER_BAD_HOST_ERROR to the client, and then closes the socket. This is different from just closing abruptly a socket (like in a crash) : the former should be reported by the client as "Can't get hostname for your address", while the later is reported as "MySQL has gone away".
Whether the client connector actually treat ER_BAD_HOST_ERROR and a socket closed differently is another story
Given that this failure overall seems related to DNS lookups, I would check the following items:
See how many rows are in the performance_schema.host_cache table.
Compare this with the size of the host cache, see the host_cache_size system variable.
If the host cache appear full, consider increasing its size: this will reduce the number of DNS calls overall, relieving pressure on DNS, in hope (admittedly, this is just a shot in the dark) that DNS transient failures will disappear.
323 out of 55 million connections indeed seems transient. Assuming the monitoring client sometime do get connected properly, inspect the row in table host_cache for this client: it may contains other failures reported.
Table performance_schema.host_cache documentation:
https://dev.mysql.com/doc/refman/5.7/en/host-cache-table.html
Further readings:
http://marcalff.blogspot.com/2012/04/performance-schema-nailing-host-cache.html
[Edit 2] Based on the new data available:
The Aborted_clients status variable shows some connections forcefully closed by the server. This typically happens when a session is idle for a very long time.
A typical scenario for this to happen is:
A client opens a connection, and sends some queries
Then the client does nothing for an extended amount of time (greater than the net_read_timeout)
Due to lack of traffic, the server closes the session, and increments Aborted_connects
The client then sends another query, sees a closed connection, and reports "MySQL has gone away"
Note that a client application forgetting to cleanly close sessions will execute 1-3, this could be the case for Aborted_clients on the master. Some cleanup here to fix clients applications using the master would help to decrease resource consumption, as leaving 151650 sessions open to die on timeout has a cost.
A client application executing 1-4 can cause Aborted_clients on the server and MySQL has gone away on the client. The client application reporting "MySQL has gone away" is most likely the culprit here.
If a monitoring application, say, checks the server every N seconds, then make sure the timeouts (here 30 and 60 sec) are significantly greater that N, or the server will kill the monitoring session.
Related
I want my consumers to process large batches, so I aim to have the consumer listener "awake", say, on 1800mb of data or every 5min, whichever comes first.
Mine is a kafka-springboot application, the topic has 28 partitions, and this is the configuration I explicitly change:
Parameter
Value I set
Default Value
Why I set it this way
fetch.max.bytes
1801mb
50mb
fetch.min.bytes+1mb
fetch.min.bytes
1800mb
1b
desired batch size
fetch.max.wait.ms
5min
500ms
desired cadence
max.partition.fetch.bytes
1801mb
1mb
unbalanced partitions
request.timeout.ms
5min+1sec
30sec
fetch.max.wait.ms + 1sec
max.poll.records
10000
500
1500 found too low
max.poll.interval.ms
5min+1sec
5min
fetch.max.wait.ms + 1sec
Nevertheless, I produce ~2gb of data to the topic, and I see the consumer-listener (a Batch Listener) is called many times per second -- way more than desired rate.
I logged the serialized-size of the ConsumerRecords<?,?> argument, and found that it is never more than 55mb.
This hints that I was not able to set fetch.max.bytes above the default 50mb.
Any idea how I can troubleshoot this?
Edit:
I found this question: Kafka MSK - a configuration of high fetch.max.wait.ms and fetch.min.bytes is behaving unexpectedly
Is it really impossible as stated?
Finally found the cause.
There is a broker fetch.max.bytes setting, and it defaults to 55mb. I only changed the consumer preferences, unaware of the broker-side limit.
see also
The kafka KIP and the actual commit.
I'm using Apache Hive.
I created a table in Hive (similar to external table) and loaded data into the same using the LOAD DATA LOCAL INPATH './Desktop/loc1/kv1.csv' OVERWRITE INTO TABLE adih; command.
While I am able to retrieve simple data from the hive table adih (e.g. select * from adih, select c_code from adih limit 1000, etc), Hive gives me errors when I ask for data involving slight computations (e.g. select count(*) from adih, select distinct(c_code) from adih).
The Hive cli output is as shown in the following link -
hive> select distinct add_user from adih;
Query ID = latize_20161031155801_8922630f-0455-426b-aa3a-6507aa0014c6
Total jobs = 1
Launching Job 1 out of 1
Number of reduce tasks not specified. Estimated from input data size: 1
In order to change the average load for a reducer (in bytes):
set hive.exec.reducers.bytes.per.reducer=
In order to limit the maximum number of reducers:
set hive.exec.reducers.max=
In order to set a constant number of reducers:
set mapreduce.job.reduces=
Starting Job = job_1477889812097_0006, Tracking URL = http://latize-data1:20005/proxy/application_1477889812097_0006/
Kill Command = /opt/hadoop-2.7.1/bin/hadoop job -kill job_1477889812097_0006
[6]+ Stopped $HIVE_HOME/bin/hive
Hive stops displaying any further logs / actions beyond the last line of "Kill Command"
Not sure where I have gone wrong (many answers on StackOverflow tend to point back to YARN configs (environment config detailed below).
I have the log as well but it contains more than 30000 characters (Stack Overflow limit)
My hadoop environment is configured as follows -
1 Name Node & 1 Data Node. Each has 20 GB of RAM with sufficient ROM. Have allocated 13 GB of RAM for the yarn.scheduler.maximum-allocation-mb and yarn.nodemanager.resource.memory-mb each with the mapreduce.map.memory.mb being set as 4 GB and the mapreduce.reduce.memory.mb being set as 12 GB. Number of reducers is currently set to default (-1). Also, Hive is configured to run with a MySQL DB (rather than Derby).
You should set the appropriate values to the properties show in your trace,
eg: Edit the properties in hive-site.xml
<property>
<name>hive.exec.reducers.bytes.per.reducer</name>
<value>67108864</value></property>
Looks like you have set mapred.reduce.tasks = -1, which makes Hive refer to its config to decide the number of reduce tasks.
You are getting an error as the number of reducers is missing in Hive config.
Try setting it using below command:
Hive> SET mapreduce.job.reduces=XX
As per official documentation: The right number of reduces seems to be 0.95 or 1.75 multiplied by (< no. of nodes > * < no. of maximum containers per node >).
I managed to get Hive and MR to work - increased the memory configurations for all the processes involved:
Increased the RAM allocated to YARN Scheduler and maximum RAM allocated to the YARN Nodemanager (in yarn-site.xml), alongside increasing the RAM allocated to the Mapper and Reducer (in mapred-site.xml).
Also incorporated parts of the answers by #Sathiyan S and #vmorusu - set the hive.exec.reducers.bytes.per.reducer property to 1 GB of data, which directly affects the number of reducers that Hive uses (through application of its heuristic techniques).
This is not a question about query optimization. Rather, a sanity check about what to expect of data transfer rates from MySQL 5.5.27 (Amazon RDS).
When running a particularly heavy query, MySQL Workbench is showing data transfer rate of about 1MB/s and the query runs for about 420 seconds. This adds up to about 420M bytes of data being transferred.
If this data is saved into a simple text file, the size of the file ends up being less than 7M bytes. I certainly expected to see some overhead due to metadata of the ResultSet, JDBC driver mechanisms, etc. But 420M vs. 7M seems like an extraordinary terrible ratio to me. Or, is this normal?
Any feedback is much appreciated.
Much thanks!
PS. More details:
-the JDBC Driver is mysql-connector-java-5.1.13
-the data is transferred between Amazon RDS and an EC2 instance
-Java 1.6 PreparedStatement is used to execute the query
Wireshark is a wonderful free and open-source (GPL) network analysis tool that can be used to great effect in cases like this. I ran the following test to see how much traffic a "typical" JDBC connection to a "normal" MySQL server might generate.
I created a table named jdbctest in MySQL (5.5.29-0ubuntu0.12.04.2) on my test server.
CREATE TABLE `jdbctest` (
`id` int(11) DEFAULT NULL,
`textcol` varchar(6) DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=latin1;
I populated it with 100,000 rows of the form
id textcol
------ -------
1 ABCDEF
2 ABCDEF
3 ABCDEF
...
100000 ABCDEF
At 4 bytes per id value and 6 bytes per textcol value, retrieving all 100,000 rows should represent somewhere on the order of 1 MB of data.
I fired up Wireshark, started a trace, and ran the following Java code which uses mysql-connector-java-5.1.26:
import java.sql.*;
public class mysqlTestMain {
static Connection dbConnection = null;
public static void main(String[] args) {
try {
String myConnectionString = "";
myConnectionString =
"jdbc:mysql://192.168.1.3:3306/mytestdb";
dbConnection = DriverManager.getConnection(myConnectionString, "root", "whatever");
PreparedStatement stmt = dbConnection.prepareStatement("SELECT * FROM jdbctest");
ResultSet rs = stmt.executeQuery();
int i = 0;
int j = 0;
String s = "";
while (rs.next()) {
i++;
j = rs.getInt("id");
s = rs.getString("textcol");
}
System.out.println(String.format("Finished reading %d rows.", i));
rs.close();
stmt.close();
dbConnection.close();
} catch (SQLException ex) {
ex.printStackTrace();
}
}
}
The console output confirmed that I had retrieved all 100,000 rows.
Looking at the summary of the Wireshark trace, I found:
Packets captured: 1811
Avg. packet size: 992.708 bytes
Bytes: 1797795
The breakdown by direction was
packets bytes
------- -----
from me to server 636 36519
from server to me 1175 1761276
So it appears that to retrieve my ~1 MB of data I received 1.72 MB of total network traffic from the MySQL server. That ~72% overhead on the download (or ~76% including traffic in both directions) is certainly nowhere near the ~5900% overhead suggested by your (rate * time) calculation.
I strongly suspect that the ~1 MB/s rate being reported by MySQL Workbench is not the overall average transfer rate over the entire time. The best way to determine the overhead in your particular circumstance would be to use a tool like Wireshark and measure it yourself.
I am new to Cassandra and just run a cassandra cluster (version 1.2.8) with 5 nodes, and I have created several keyspaces and tables on there. However, I found all data are stored in one node (in the below output, I have replaced ip addresses by node numbers manually):
Datacenter: 105
==========
Address Rack Status State Load Owns Token
4
node-1 155 Up Normal 249.89 KB 100.00% 0
node-2 155 Up Normal 265.39 KB 0.00% 1
node-3 155 Up Normal 262.31 KB 0.00% 2
node-4 155 Up Normal 98.35 KB 0.00% 3
node-5 155 Up Normal 113.58 KB 0.00% 4
and in their cassandra.yaml files, I use all default settings except cluster_name, initial_token, endpoint_snitch, listen_address, rpc_address, seeds, and internode_compression. Below I list those non-ip address fields I modified:
endpoint_snitch: RackInferringSnitch
rpc_address: 0.0.0.0
seed_provider:
- class_name: org.apache.cassandra.locator.SimpleSeedProvider
parameters:
- seeds: "node-1, node-2"
internode_compression: none
and all nodes using the same seeds.
Can I know where I might do wrong in the config? And please feel free to let me know if any additional information is needed to figure out the problem.
Thank you!
If you are starting with Cassandra 1.2.8 you should try using the vnodes feature. Instead of setting the initial_token, uncomment # num_tokens: 256 in the cassandra.yaml, and leave initial_token blank, or comment it out. Then you don't have to calculate token positions. Each node will randomly assign itself 256 tokens, and your cluster will be mostly balanced (within a few %). Using vnodes will also mean that you don't have to "rebalance" you cluster every time you add or remove nodes.
See this blog post for a full description of vnodes and how they work:
http://www.datastax.com/dev/blog/virtual-nodes-in-cassandra-1-2
Your token assignment is the problem here. An assigned token are used determines the node's position in the ring and the range of data it stores. When you generate tokens the aim is to use up the entire range from 0 to (2^127 - 1). Tokens aren't id's like with mysql cluster where you have to increment them sequentially.
There is a tool on git that can help you calculate the tokens based on the size of your cluster.
Read this article to gain a deeper understanding of the tokens. And if you want to understand the meaning of the numbers that are generated check this article out.
You should provide a replication_factor when creating a keyspace:
CREATE KEYSPACE demodb
WITH REPLICATION = {'class' : 'SimpleStrategy', 'replication_factor': 3};
If you use DESCRIBE KEYSPACE x in cqlsh you'll see what replication_factor is currently set for your keyspace (I assume the answer is 1).
More details here
We are using DBCP inside a Grails application. The database is on another server, so TCP/IP is in play here. We have monitored the database by doing a show processlist frequently, and we never see above 50 connections. However, the sockets on the client grow enormously (at one point I saw over 2700). Most of them are in TIME_WAIT status.
So eventually we get a NoRouteToHostException, because it cannot open a socket.
Note that we hit the database over 40,000 times in less than a minute in this use case.
Does anyone have suggestions as to why this might be? I would think that, since our connection pool is limited to 100 (and we only see about 50 connections open), I'd only see slightly more than 50, since occasionally one might get stale. But we're seeing thousands. Is this expected? Or any other tips about something we might be missing when looking at this situation?
Here are the dbcp settings we are using:
properties {
maxActive = 100
maxIdle = 4
minIdle = 1
initialSize = 1
minEvictableIdleTimeMillis = 60000
timeBetweenEvictionRunsMillis = 60000
maxWait = 10000
removeAbandoned = true
removeAbandonedTimeout = 60
validationQuery = "/* PING */ SELECT 1"
testOnBorrow = true
testWhileIdle = true
numTestsPerEvictionRun = -1
logAbandoned = true
}
Also note that we use autoReconnect=true on the connection string, although we are considering dropping it (we get stale connections overnight otherwise).
Thanks!
Ok, so I was able to sort it out. Turns out I was misunderstanding the maxIdle and how it works.
Anything returned to the pool above maxIdle is immediately released. So most of the connections were being closed and reopened, hence why the sockets were exhausted.