I want to migrate my app angular4 to angular5, but it's looks ng version have some issue with latest version.
Any Idea what is the stable version for angular5. #angular/cli.
Step I followed:
Installed latest version of node 8.9.1
npm install -g #angular/cli#latest
ng -v
_ _ ____ _ ___
/ \ _ __ __ _ _ _| | __ _ _ __ / ___| | |_ _|
/ △ \ | '_ \ / _` | | | | |/ _` | '__| | | | | | |
/ ___ \| | | | (_| | |_| | | (_| | | | |___| |___ | |
/_/ \_\_| |_|\__, |\__,_|_|\__,_|_| \____|_____|___|
|___/
Angular CLI: 1.5.5
Node: 8.9.1
OS: darwin x64
Angular: error
... animations, cli, common, compiler, compiler-cli, core, forms
... http, platform-browser, platform-browser-dynamic, router
typescript: error
webpack: error
it's work after install npm install typescript#2.4.2 --save-exact ...
Thanks.! – Umang Savaliya Dec 7 '17 at 9:34
Solved in their comments by checking the dependencies are up to date.
npm install typescript#2.4.2 --save-exact with Angular 5.1 with Angular-CLI v1.6.0
Resolve this issue.
Related
TF Version : 2.4.1
CUDA Version : 11.1
tf.test_is_gpu_available() -- returns --> FALSE
tf.test.is_built_with_cuda() -- returns --> TRUE
I tried to revert back TF to 2.4.0, but didn't work
I have also tried:
$ pip uninstall tensorflow
$ pip install tensorflow-gpu
But nothing seems to work, TF is just not detecting my GPUs
EDIT 1:
Output of nvcc --version:
nvcc: NVIDIA (R) Cuda compiler driver
Copyright (c) 2005-2020 NVIDIA Corporation
Built on Mon_Oct_12_20:09:46_PDT_2020
Cuda compilation tools, release 11.1, V11.1.105
Build cuda_11.1.TC455_06.29190527_0
Output of nvidia-smi
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 460.73.01 Driver Version: 460.73.01 CUDA Version: 11.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 GeForce RTX 3090 Off | 00000000:01:00.0 Off | N/A |
| 30% 35C P8 23W / 300W | 23MiB / 24268MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 1 GeForce RTX 3090 Off | 00000000:43:00.0 Off | N/A |
| 30% 40C P8 27W / 300W | 5MiB / 24268MiB | 0% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
| 2 GeForce RTX 3090 Off | 00000000:81:00.0 Off | N/A |
| 64% 63C P2 179W / 300W | 24043MiB / 24268MiB | 59% Default |
| | | N/A |
+-------------------------------+----------------------+----------------------+
+-----------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=============================================================================|
| 0 N/A N/A 2362 G /usr/lib/xorg/Xorg 9MiB |
| 0 N/A N/A 2564 G /usr/bin/gnome-shell 12MiB |
| 1 N/A N/A 2362 G /usr/lib/xorg/Xorg 4MiB |
| 2 N/A N/A 2362 G /usr/lib/xorg/Xorg 4MiB |
| 2 N/A N/A 14304 C python3 24035MiB |
+-----------------------------------------------------------------------------+
While running tf.test.is_gpu_avaliable(), I get the following warning:
WARNING:tensorflow:From Spell_correction.py:35: is_gpu_available (from tensorflow.python.framework.test_util) is deprecated and will be removed in a future version.
Instructions for updating:
Use `tf.config.list_physical_devices('GPU')` instead.
2021-05-07 21:46:21.855460: I tensorflow/compiler/jit/xla_gpu_device.cc:99] Not creating XLA devices, tf_xla_enable_xla_devices not set
2021-05-07 21:46:21.856690: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1720] Found device 0 with properties:
pciBusID: 0000:43:00.0 name: GeForce RTX 3090 computeCapability: 8.6
coreClock: 1.695GHz coreCount: 82 deviceMemorySize: 23.70GiB deviceMemoryBandwidth: 871.81GiB/s
2021-05-07 21:46:21.856716: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudart.so.11.0
2021-05-07 21:46:21.856735: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublas.so.11
2021-05-07 21:46:21.856747: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcublasLt.so.11
2021-05-07 21:46:21.856759: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcufft.so.10
2021-05-07 21:46:21.856771: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcurand.so.10
2021-05-07 21:46:21.856829: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcusolver.so.10'; dlerror: libcusolver.so.10: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/cuda-11.1/lib64
2021-05-07 21:46:21.856846: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcusparse.so.11
2021-05-07 21:46:21.856856: I tensorflow/stream_executor/platform/default/dso_loader.cc:49] Successfully opened dynamic library libcudnn.so.8
2021-05-07 21:46:21.856863: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1757] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
2021-05-07 21:46:21.942589: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1261] Device interconnect StreamExecutor with strength 1 edge matrix:
2021-05-07 21:46:21.942626: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1267] 0
2021-05-07 21:46:21.942633: I tensorflow/core/common_runtime/gpu/gpu_device.cc:1280] 0: N
Another Observation:
Pytorch is detecting GPU, while TF is not.
torch.cuda.is_available() --> TRUE
tf.test.is_gpu_available() --> FALSE
if you use ubuntu 20.04, I suggest to follow steps from here. I recently had the same problem.
You have
NVIDIA-SMI 460.73.01 Driver Version: 460.73.01 CUDA Version: 11.2 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|===============================+======================+======================|
| 0 GeForce RTX 3090 Off | 00000000:01:00.0 Off | N/A |
| 30% 35C P8 23W / 300W | 23MiB / 24268MiB | 0% Default |
| | | N/A
try to get latest version of NVIDIA 465 and Cuda 11.3. For my case nvidia-smi is as below:
+-----------------------------------------------------------------------------+
| NVIDIA-SMI 465.19.01 Driver Version: 465.19.01 CUDA Version: 11.3 |
|-------------------------------+----------------------+----------------------+
| GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
What I did;
(1) I uninstalled NVIDIA and CUDA completely see here and be careful.
sudo apt-get remove --purge '^nvidia-.*'
sudo apt-get install ubuntu-desktop
sudo rm /etc/X11/xorg.conf
echo 'nouveau' | sudo tee -a /etc/modules
(2) I downloaded NVIDIA, download .run file and simply run sudo bash NVIDIA*.run
(3) I downloaded cuDNN and perform following as described here
tar -xzvf cudnn-11.3-.*.tgz
sudo cp cuda/include/cudnn.h /usr/local/cuda/include
sudo cp cuda/lib64/libcudnn* /usr/local/cuda/lib64
sudo chmod a+r /usr/local/cuda/include/cudnn.h /usr/local/cuda/lib64/libcudnn*
Also check .bashrc files as well as described here:
cd ~
gedit .bashrc or nano .bashrc
#add this in the end :
export PATH=/usr/local/cuda/bin${PATH:+:${PATH}}
export PATH=/usr/local/cuda-11.3/bin${PATH:+:${PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda-11.3/lib64\${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
export LD_LIBRARY_PATH=/usr/local/cuda11.3/targets/x86_64linux\${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
Then, pip install tensorflow-gpu==2.4.1
Running Spark locally spark-sql or through pyspark spark.sql(...), if I use a CTE in a query and then reference the CTE with an incorrect namespace / database, the query works just fine (unexpected). When I run the query in production (on Databricks), I get a Table or view not found error (expected).
Unexpected pass behavior can be reproduced locally via spark-sql:
WITH myview AS (
SELECT 1 AS column
)
SELECT
*
FROM
invalid_namespace.myview;
Which returns "1" when I expect it to fail.
Can someone help me make this fail locally so that we can properly test before we deploy?
Exact steps to reproduce from a terminal:
$ spark-sql
...
spark-sql> WITH some_new_cte AS (SELECT 1 AS column)
> SELECT * FROM namespace_does_not_exist.some_new_cte;
...
1
Time taken: 2.294 seconds, Fetched 1 row(s)
spark-sql>
If you look at the query plan, it actually failed to parse
== Parsed Logical Plan ==
CTE [myview]
: +- SubqueryAlias `myview`
: +- Project [1 AS column#0]
: +- OneRowRelation
+- 'Project [*]
+- 'UnresolvedRelation `invalid_namespace`.`myview`
== Analyzed Logical Plan ==
column: int
Project [column#0]
+- SubqueryAlias `myview`
+- Project [1 AS column#0]
+- OneRowRelation
== Optimized Logical Plan ==
Project [1 AS column#0]
+- OneRowRelation
== Physical Plan ==
*(1) Project [1 AS column#0]
+- Scan OneRowRelation[]
The reason your query returned "1" was because spark saw that your view was in the same query, so it just ignored your namespace. If the namespace really doesn't exist, it will fail.
This seems to be a bug that affects versions of Spark 2.4.0 through 2.4.5 (I did not check <2.4.0). It appears to have been fixed in 2.4.6 and continues to work as expected in 3.0.0.
Unexpected success in 2.4.0:
$ spark-submit --version
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 2.4.0
/_/
Using Scala version 2.11.12, OpenJDK 64-Bit Server VM, 1.8.0_262
Branch
Compiled by user on 2018-10-29T06:22:05Z
Revision
Url
Type --help for more information.
$ echo "WITH mycte AS (SELECT 1 AS column) SELECT * FROM bad_namespace.mycte;" | SPARK_CONF_DIR=spark_conf spark-sql
20/07/17 10:59:05 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Spark master: local[*], Application Id: local-1595008748636
spark-sql> WITH mycte AS (SELECT 1 AS column) SELECT * FROM bad_namespace.mycte;
1
Time taken: 1.822 seconds, Fetched 1 row(s)
spark-sql>
Tested but unshown: 2.4.1, 2.4.2, 2.4.3, 2.4.4 (all succeed unexpectedly)
Unexpected success in 2.4.5:
$ spark-submit --version
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 2.4.5
/_/
Using Scala version 2.11.12, OpenJDK 64-Bit Server VM, 1.8.0_262
Branch HEAD
Compiled by user centos on 2020-02-02T19:38:06Z
Revision cee4ecbb16917fa85f02c635925e2687400aa56b
Url https://gitbox.apache.org/repos/asf/spark.git
Type --help for more information.
$ echo "WITH mycte AS (SELECT 1 AS column) SELECT * FROM bad_namespace.mycte;" | SPARK_CONF_DIR=spark_conf spark-sql
20/07/17 10:59:55 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Spark master: local[*], Application Id: local-1595008798737
spark-sql> WITH mycte AS (SELECT 1 AS column) SELECT * FROM bad_namespace.mycte;
1
Time taken: 2.155 seconds, Fetched 1 row(s)
spark-sql>
Expected failure in 2.4.6:
$ spark-submit --version
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 2.4.6
/_/
Using Scala version 2.11.12, OpenJDK 64-Bit Server VM, 1.8.0_262
Branch HEAD
Compiled by user holden on 2020-05-29T23:47:51Z
Revision 807e0a484d1de767d1f02bd8a622da6450bdf940
Url https://gitbox.apache.org/repos/asf/spark.git
Type --help for more information.
$ echo "WITH mycte AS (SELECT 1 AS column) SELECT * FROM bad_namespace.mycte;" | SPARK_CONF_DIR=spark_conf spark-sql
20/07/17 11:00:40 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Spark master: local[*], Application Id: local-1595008843321
spark-sql> WITH mycte AS (SELECT 1 AS column) SELECT * FROM bad_namespace.mycte;
20/07/17 11:00:44 WARN ObjectStore: Failed to get database global_temp, returning NoSuchObjectException
20/07/17 11:00:44 WARN ObjectStore: Failed to get database bad_namespace, returning NoSuchObjectException
Error in query: Table or view not found: `bad_namespace`.`mycte`; line 1 pos 49;
'Project [*]
+- 'UnresolvedRelation `bad_namespace`.`mycte`
spark-sql>
Expected failure in 3.0.0:
$ spark-submit --version
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 3.0.0
/_/
Using Scala version 2.12.10, OpenJDK 64-Bit Server VM, 1.8.0_262
Branch HEAD
Compiled by user ubuntu on 2020-06-06T11:32:25Z
Revision 3fdfce3120f307147244e5eaf46d61419a723d50
Url https://gitbox.apache.org/repos/asf/spark.git
Type --help for more information.
$ echo "WITH mycte AS (SELECT 1 AS column) SELECT * FROM bad_namespace.mycte;" | SPARK_CONF_DIR=spark_conf spark-sql
20/07/17 11:01:40 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
20/07/17 11:01:42 WARN HiveConf: HiveConf of name hive.stats.jdbc.timeout does not exist
20/07/17 11:01:42 WARN HiveConf: HiveConf of name hive.stats.retries.wait does not exist
20/07/17 11:01:44 ERROR ObjectStore: Version information found in metastore differs 1.2.0 from expected schema version 2.3.0. Schema verififcation is disabled hive.metastore.schema.verification
20/07/17 11:01:44 WARN ObjectStore: setMetaStoreSchemaVersion called but recording version is disabled: version = 2.3.0, comment = Set by MetaStore georgeleslie-waksman#10.0.1.178
Spark master: local[*], Application Id: local-1595008901594
spark-sql> WITH mycte AS (SELECT 1 AS column) SELECT * FROM bad_namespace.mycte;
20/07/17 11:01:45 WARN ObjectStore: Failed to get database global_temp, returning NoSuchObjectException
20/07/17 11:01:45 WARN ObjectStore: Failed to get database bad_namespace, returning NoSuchObjectException
Error in query: Table or view not found: bad_namespace.mycte; line 1 pos 49;
'Project [*]
+- 'UnresolvedRelation [bad_namespace, mycte]
spark-sql>
I'm using the ng cli for the first time. I'm trying to make a new module ('foo') and a new component ('bar') under the foo module. Though, how I think I'm supposed to do it in ng cli doesn't seem to work:
mbp:my-new-app chris$ ng g m foo
installing module
create src/app/foo/foo.module.ts
mbp:my-new-app chris$ ng g c bar -m foo
installing component
create src/app/bar/bar.component.scss
create src/app/bar/bar.component.html
create src/app/bar/bar.component.spec.ts
create src/app/bar/bar.component.ts
EISDIR: illegal operation on a directory, read
Error: EISDIR: illegal operation on a directory, read
at Error (native)
at Object.fs.readSync (fs.js:732:19)
at tryReadSync (fs.js:487:20)
at Object.fs.readFileSync (fs.js:535:19)
at Class.afterInstall (/Users/chris/code/my-new-app/node_modules/#angular/cli/blueprints/component/index.js:209:34)
at tryCatch (/Users/chris/code/my-new-app/node_modules/rsvp/dist/rsvp.js:539:12)
at invokeCallback (/Users/chris/code/my-new-app/node_modules/rsvp/dist/rsvp.js:554:13)
at publish (/Users/chris/code/my-new-app/node_modules/rsvp/dist/rsvp.js:522:7)
at flush (/Users/chris/code/my-new-app/node_modules/rsvp/dist/rsvp.js:2414:5)
at _combinedTickCallback (internal/process/next_tick.js:73:7)
ng cli version:
mbp:my-new-app chris$ ng version
_ _ ____ _ ___
/ \ _ __ __ _ _ _| | __ _ _ __ / ___| | |_ _|
/ △ \ | '_ \ / _` | | | | |/ _` | '__| | | | | | |
/ ___ \| | | | (_| | |_| | | (_| | | | |___| |___ | |
/_/ \_\_| |_|\__, |\__,_|_|\__,_|_| \____|_____|___|
|___/
#angular/cli: 1.0.0
node: 6.10.1
os: darwin x64
#angular/common: 4.0.1
#angular/compiler: 4.0.1
#angular/core: 4.0.1
#angular/forms: 4.0.1
#angular/http: 4.0.1
#angular/platform-browser: 4.0.1
#angular/platform-browser-dynamic: 4.0.1
#angular/router: 4.0.1
#angular/cli: 1.0.0
#angular/compiler-cli: 4.0.1
Am I doing using this wrong? I haven't found documentation specifically on this feature.
Thanks!
instead of running
ng g c bar -m foo
try to run (without -m)
ng g c foo/bar
if you want to reference a module, which should export/import your new component, you should provide a relative path to this module, like:
ng g c bar -m foo/foo.module
in this case bar component will be imported/exported by foo.module, but located under src/app.
EASDIR error occurred because you provided a directory (foo) instead of file (foo/foo.module)
as answered for example here:
EISDIR means that the target of the operation is a directory in reality but that the expected filetype of the target is something other than a directory.
I recently updated my global A2 CLI, as well as an existing project, to:
_ _ _
__ _ _ __ __ _ _ _ | | __ _ _ __ ___ | |(_)
/ _` || '_ \ / _` || | | || | / _` || '__|_____ / __|| || |
| (_| || | | || (_| || |_| || || (_| || | |_____|| (__ | || |
\__,_||_| |_| \__, | \__,_||_| \__,_||_| \___||_||_|
|___/
#angular/cli: 1.0.0-beta.30
node: 7.4.0
os: darwin x64
#angular/common: 2.4.6
#angular/compiler: 2.4.6
#angular/core: 2.4.6
#angular/forms: 2.4.6
#angular/http: 2.4.6
#angular/platform-browser: 2.4.6
#angular/platform-browser-dynamic: 2.4.6
#angular/router: 3.4.6
#angular/cli: 1.0.0-beta.30
#angular/compiler-cli: 2.4.6
When I spin up ng serve on the project it runs fine but when I upload it to my vm I get the following errors:
[Error] SyntaxError: Unexpected token '<'
(anonymous function) (inline.bundle.js:1)
[Error] SyntaxError: Unexpected token '<'
(anonymous function) (polyfills.bundle.js:1)
[Error] ReferenceError: Can't find variable: webpackJsonp
Global Code (styles.bundle.js:1)
[Error] SyntaxError: Unexpected token '<'
(anonymous function) (vendor.bundle.js:1)
[Error] ReferenceError: Can't find variable: webpackJsonp
Global Code (main.bundle.js:1)
This morning I created a new project and uploaded it to the vm without additional changes, to see if it was something in the project update, and I get the same errors.
Pretty stumped on what's going on here. This is the first time I've encountered it and my projects have worked fine locally and remotely before updating.
The remote system is a Windows Server 2012 with XAMPP.
My local system is a Mac, usually running the app via ng serve, but checked with MAMP and it works under Apache there, too.
Has anyone run across this?
So evidently it had something to do with the directory. The app runs in a subdirectory on my vm and that hasn't posed a problem in the past. When I changed the bas href from "/" to "./", it worked again.
I try to use rabbit on ubuntu 12.04. After installation rabbitmq-server works fine. Than I stop it and add my configuration file.
root#rabbit1:~# tail /etc/rabbitmq/rabbitmq-env.conf
RABBITMQ_CONFIG_FILE=/etc/rabbitmq/myrabbitmq
root#rabbit1:~# tail /etc/rabbitmq/myrabbitmq.config
[{rabbit,
[{cluster_nodes, {['rabbit#rabbit1', 'rabbit#rabbit2'], disc}}]}].
With this files rabbitmq-server says on start:
root#rabbit1:~# rabbitmq-server
Activating RabbitMQ plugins ...
0 plugins activated:
+---+ +---+
| | | |
| | | |
| | | |
| +---+ +-------+
| |
| RabbitMQ +---+ |
| | | |
| v2.7.1 +---+ |
| |
+-------------------+
AMQP 0-9-1 / 0-9 / 0-8
Copyright (C) 2007-2011 VMware, Inc.
Licensed under the MPL. See http://www.rabbitmq.com/
node : rabbit#rabbit1
app descriptor : /usr/lib/rabbitmq/lib/rabbitmq_server-2.7.1/sbin/../ebin/rabbit.app
home dir : /var/lib/rabbitmq
config file(s) : /etc/rabbitmq/myrabbitmq.config
cookie hash : 31CaH3BCSDNL1hDIFQzH2Q==
log : /var/log/rabbitmq/rabbit#rabbit1.log
sasl log : /var/log/rabbitmq/rabbit#rabbit1-sasl.log
database dir : /var/lib/rabbitmq/mnesia/rabbit#rabbit1
erlang version : 5.8.5
-- rabbit boot start
starting file handle cache server ...done
starting worker pool ...done
starting database ...BOOT ERROR: FAILED
Reason: function_clause
Stacktrace: [{lists,usort,[{[rabbit#rabbit1,rabbit#rabbit2],disc}]},
{rabbit_mnesia,init_db,3},
{rabbit_mnesia,init,0},
{rabbit,'-run_boot_step/1-lc$^1/1-1-',1},
{rabbit,run_boot_step,1},
{rabbit,'-start/2-lc$^0/1-0-',1},
{rabbit,start,2},
{application_master,start_it_old,4}]
Erlang has closed
{"Kernel pid terminated",application_controller,"{application_start_failure,rabbit,{bad_return,{{rabbit,start,[normal,[]]},{'EXIT',{rabbit,failure_during_boot}}}}}"}
Kernel pid terminated (application_controller) ({application_start_failure,rabbit,{bad_return,{{rabbit,start,[normal,[]]},{'EXIT',{rabbit,failure_during_boot}}}}})
Have any suggestion what's wrong with my rabbit?
Configuration file should be like this:
root#rabbit1:~# cat /etc/rabbitmq/myrabbitmq.config
[{rabbit,
[{cluster_nodes, ['rabbit#rabbit1', 'rabbit#rabbit2'] }]}].
It seems, that disc or ram node configures in different way than in documentation to latest version of rabbit. In this configuration two disc nodes will be created. If somebody wants ram node this node should be ommitted in configuration of this node (not in other config files).