Blog do projektu Open Source JavaHotel

sobota, 28 października 2017

Next version of Civilization The Board Game

I deployed next version of my computer implementation of  Civilization The Board Game. The implementation consists of three parts:
New features
  • spend trade for production and undo spend
  • scout can send production to the city and undo sending
  • buying units
Spend trade for production

Just specify the number of production you want to get and the trade is reduced accordingly. So you can do shopping as you wish.The player can also undo the last spending unless it is used.
Send production from square to the city

Click the city and choose the scout you want to send production.
The player can also undo this action unless production is spent.
Click Undo button right to the grayed "Send Production" button.
Buying units

The player can buy units although the battle is not implemented yet. The unit panel shows only the number of units of a particular type. After clicking the panel, the detailed list of units including their strength is revealed. Of course, this option is not available for opposite player. Also, in the market panel, any player can see the detailed list of killed units but not the units still waiting to be taken.
Next steps
  • Resource harvesting including friendly villages
  • Battle

czwartek, 26 października 2017

HDP, BigInsights, Kafka, Kerberos

I spent several hours resolving a nasty problem which came up after enabling Kerberos security. Suddenly command line kafka-topic utility tools refused to cooperate:
[2017-10-26 23:31:17,424] WARN Could not login: the client is being asked for a password, but the Zookeeper client code does not currently support obtaining a password from the user. Make sure that the client is configured to use a ticket cache (using the JAAS configuration setting 'useTicketCache=true)' and restart the client. If you still get this message after that, the TGT in the ticket cache has expired and must be manually refreshed. To do so, first determine if you are using a password or a keytab. If the former, run kinit in a Unix shell in the environment of the user who is running this Zookeeper client using the command 'kinit ' (where  is the name of the client's Kerberos principal). If the latter, do 'kinit -k -t  ' (where  is the name of the Kerberos principal, and  is the location of the keytab file). After manually refreshing your cache, restart this client. If you continue to see this message after manually refreshing your cache, ensure that your KDC host's clock is in sync with this host's clock. (org.apache.zookeeper.client.ZooKeeperSaslClient)
[2017-10-26 23:31:17,426] WARN SASL configuration failed: No password provided Will continue connection to Zookeeper server without SASL authentication, if Zookeeper server allows it. (org.apache.zookeeper.ClientCnxn)
Exception in thread "main" org.I0Itec.zkclient.exception.ZkAuthFailedException: Authentication failure
 at org.I0Itec.zkclient.ZkClient.waitForKeeperState(
 at org.I0Itec.zkclient.ZkClient.waitUntilConnected(
 at org.I0Itec.zkclient.ZkClient.connect(
 at org.I0Itec.zkclient.ZkClient.(
 at org.I0Itec.zkclient.ZkClient.(
 at kafka.utils.ZkUtils$.createZkClientAndConnection(ZkUtils.scala:76)
 at kafka.utils.ZkUtils$.apply(ZkUtils.scala:58)
 at kafka.admin.TopicCommand$.main(TopicCommand.scala:53)
 at kafka.admin.TopicCommand.main(TopicCommand.scala)

The reason is quite simple. Kafka to communicate with underlying Zookeper uses /etc/security/keytabs/kafka.service.keytab. As a default, this file has permission 400 so only kafka user can access it.
The solution is to change permission to 440, so the security is softened a little bit but the file is still protected. User vying to create Kafka topic should belong to hadoop group.

poniedziałek, 9 października 2017

Hadoop and SQL engines

Every Hadoop distribution comes with several SQL engines. So I decided to create a simple test to compare them. Run the same queries against the same data set. So far I have been working with two Hadoop distribution, BigInsights 4.x and HDP 2.6.2 with Big SQL 5.0.1. The second is now the successor of BigInsights.
I was comparing the following SQL engines:

  • MySQL, embedded
  • Hive against data in different format: text files, Parquet and OCR
  • Big SQL on Hive tables, Parquet and OCR
  • Spark SQL
  • Phoenix, SQL engine for HBase.
It is not any kind of benchmarking, the purpose is not to prove the superiority of one SQL engine over another. I also haven't done any kind of tunning or reconfiguration to speed up. Just to conduct a simple check after installation and have several numbers at hand.
The test description and several results are here.
Although I do not claim any ultimate authority here, I can provide several conclusions.
  • Big SQL is a winner. Particularly comparing to Hive. Very important: Big SQL is running on the same physical data, the only difference is a different computational model. It even beats MySQL. But, of course, MySQL will get the upper hand for OLTP requests. 
  • Hive behaves much better paired with TEZ. On the other hand, the execution time is very fluid, can change from one execution to another drastically.
  • Spark SQL is outside competition but it is hard to outmatch in-memory execution.
  • Phoenix SQL is at the end of the race, but the execution time is very stable.