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  • Best books on Managing a Software Development Team? [closed]

    - by JohnFx
    The canonical books on software development is fairly well established. However, after reading through a dreadful book full of bad advice on managing programming teams this weekend I am looking for recommendations for really good books that focus on the management side of programming (recruiting, performance measurement/management, motivation, best practices, organizational structure, etc.) and not as much on the construction of software itself. Any suggestions?

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  • Top 6 Methods of Link Building

    Link building is single most important strategy for effective search engine optimization. With tons of websites being added to the World Wide Web everyday, it is very important to keep your website popular by creating high value back links. Beginners commit very obvious mistakes in their link building practices which can be easily avoided if one follows the recommendations.

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  • Web Directory Submission - Important Part in Link Building

    Submitting to web directories is a vital part of every link building strategy. Apart from driving traffic to your website via direct recommendations, web directories offer static, one way links to your website, boosting your link popularity and improving your rankings on the major search engines. Search engine optimization has started turning submission to directories and articles to its advantage.

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  • What kind of process should I use to learn a big system?

    - by user394128
    I just joined a new company and started to study one of the their bigger system. For me to be productive, I need to understand the entire system without too much help. Other programers are really busy and dont' have time to hold my hands. I used to use brain map to draw a pictorial representation of the system. Any recommendations on what is the right appproach to dissect a big program? It is a .net prgoram by the way.

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  • Should I use the ATI proprietary or free drivers with two Crossfire HD5850s?

    - by Dekel
    I own 2 XFX Radeon HD 5850 in crossfire configuration connected to 3 24" monitors. I really want to make Ubuntu my daily OS but can't seem to find the best configuration to use. Some threads say that the free driver is better then the ATI one and some say the new Catalyst fully takes advantage of the card capabilities. Anyone out there with a similar setup? What are your recommendations for a good production in 12.04 setup?

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  • Building Your Own Website

    Here we discuss what you do and don't need when building your own website. We also give you recommendations on what to use to save a lot of money, time, and frustration.

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  • High Load mysql on Debian server stops every day. Why?

    - by Oleg Abrazhaev
    I have Debian server with 32 gb memory. And there is apache2, memcached and nginx on this server. Memory load always on maximum. Only 500m free. Most memory leak do MySql. Apache only 70 clients configured, other services small memory usage. When mysql use all memory it stops. And nothing works, need mysql reboot. Mysql configured use maximum 24 gb memory. I have hight weight InnoDB bases. (400000 rows, 30 gb). And on server multithread daemon, that makes many inserts in this tables, thats why InnoDB. There is my mysql config. [mysqld] # # * Basic Settings # default-time-zone = "+04:00" user = mysql pid-file = /var/run/mysqld/mysqld.pid socket = /var/run/mysqld/mysqld.sock port = 3306 basedir = /usr datadir = /var/lib/mysql tmpdir = /tmp language = /usr/share/mysql/english skip-external-locking default-time-zone='Europe/Moscow' # # Instead of skip-networking the default is now to listen only on # localhost which is more compatible and is not less secure. # # * Fine Tuning # #low_priority_updates = 1 concurrent_insert = ALWAYS wait_timeout = 600 interactive_timeout = 600 #normal key_buffer_size = 2024M #key_buffer_size = 1512M #70% hot cache key_cache_division_limit= 70 #16-32 max_allowed_packet = 32M #1-16M thread_stack = 8M #40-50 thread_cache_size = 50 #orderby groupby sort sort_buffer_size = 64M #same myisam_sort_buffer_size = 400M #temp table creates when group_by tmp_table_size = 3000M #tables in memory max_heap_table_size = 3000M #on disk open_files_limit = 10000 table_cache = 10000 join_buffer_size = 5M # This replaces the startup script and checks MyISAM tables if needed # the first time they are touched myisam-recover = BACKUP #myisam_use_mmap = 1 max_connections = 200 thread_concurrency = 8 # # * Query Cache Configuration # #more ignored query_cache_limit = 50M query_cache_size = 210M #on query cache query_cache_type = 1 # # * Logging and Replication # # Both location gets rotated by the cronjob. # Be aware that this log type is a performance killer. #log = /var/log/mysql/mysql.log # # Error logging goes to syslog. This is a Debian improvement :) # # Here you can see queries with especially long duration log_slow_queries = /var/log/mysql/mysql-slow.log long_query_time = 1 log-queries-not-using-indexes # # The following can be used as easy to replay backup logs or for replication. # note: if you are setting up a replication slave, see README.Debian about # other settings you may need to change. #server-id = 1 #log_bin = /var/log/mysql/mysql-bin.log server-id = 1 log-bin = /var/lib/mysql/mysql-bin #replicate-do-db = gate log-bin-index = /var/lib/mysql/mysql-bin.index log-error = /var/lib/mysql/mysql-bin.err relay-log = /var/lib/mysql/relay-bin relay-log-info-file = /var/lib/mysql/relay-bin.info relay-log-index = /var/lib/mysql/relay-bin.index binlog_do_db = 24avia expire_logs_days = 10 max_binlog_size = 100M read_buffer_size = 4024288 innodb_buffer_pool_size = 5000M innodb_flush_log_at_trx_commit = 2 innodb_thread_concurrency = 8 table_definition_cache = 2000 group_concat_max_len = 16M #binlog_do_db = gate #binlog_ignore_db = include_database_name # # * BerkeleyDB # # Using BerkeleyDB is now discouraged as its support will cease in 5.1.12. #skip-bdb # # * InnoDB # # InnoDB is enabled by default with a 10MB datafile in /var/lib/mysql/. # Read the manual for more InnoDB related options. There are many! # You might want to disable InnoDB to shrink the mysqld process by circa 100MB. #skip-innodb # # * Security Features # # Read the manual, too, if you want chroot! # chroot = /var/lib/mysql/ # # For generating SSL certificates I recommend the OpenSSL GUI "tinyca". # # ssl-ca=/etc/mysql/cacert.pem # ssl-cert=/etc/mysql/server-cert.pem # ssl-key=/etc/mysql/server-key.pem [mysqldump] quick quote-names max_allowed_packet = 500M [mysql] #no-auto-rehash # faster start of mysql but no tab completition [isamchk] key_buffer = 32M key_buffer_size = 512M # # * NDB Cluster # # See /usr/share/doc/mysql-server-*/README.Debian for more information. # # The following configuration is read by the NDB Data Nodes (ndbd processes) # not from the NDB Management Nodes (ndb_mgmd processes). # # [MYSQL_CLUSTER] # ndb-connectstring=127.0.0.1 # # * IMPORTANT: Additional settings that can override those from this file! # The files must end with '.cnf', otherwise they'll be ignored. # !includedir /etc/mysql/conf.d/ Please, help me make it stable. Memory used /etc/mysql # free total used free shared buffers cached Mem: 32930800 32766424 164376 0 139208 23829196 -/+ buffers/cache: 8798020 24132780 Swap: 33553328 44660 33508668 Maybe my problem not in memory, but MySQL stops every day. As you can see, cache memory free 24 gb. Thank to Michael Hampton? for correction. Load overage on server 3.5. Maybe hdd or another problem? Maybe my config not optimal for 30gb InnoDB ? I'm already try mysqltuner and tunung-primer.sh , but they marked all green. Mysqltuner output mysqltuner >> MySQLTuner 1.0.1 - Major Hayden <[email protected]> >> Bug reports, feature requests, and downloads at http://mysqltuner.com/ >> Run with '--help' for additional options and output filtering -------- General Statistics -------------------------------------------------- [--] Skipped version check for MySQLTuner script [OK] Currently running supported MySQL version 5.5.24-9-log [OK] Operating on 64-bit architecture -------- Storage Engine Statistics ------------------------------------------- [--] Status: -Archive -BDB -Federated +InnoDB -ISAM -NDBCluster [--] Data in MyISAM tables: 112G (Tables: 1528) [--] Data in InnoDB tables: 39G (Tables: 340) [--] Data in PERFORMANCE_SCHEMA tables: 0B (Tables: 17) [!!] Total fragmented tables: 344 -------- Performance Metrics ------------------------------------------------- [--] Up for: 8h 18m 33s (14M q [478.333 qps], 259K conn, TX: 9B, RX: 5B) [--] Reads / Writes: 84% / 16% [--] Total buffers: 10.5G global + 81.1M per thread (200 max threads) [OK] Maximum possible memory usage: 26.3G (83% of installed RAM) [OK] Slow queries: 1% (259K/14M) [!!] Highest connection usage: 100% (201/200) [OK] Key buffer size / total MyISAM indexes: 1.5G/5.6G [OK] Key buffer hit rate: 100.0% (6B cached / 1M reads) [OK] Query cache efficiency: 74.3% (8M cached / 11M selects) [OK] Query cache prunes per day: 0 [OK] Sorts requiring temporary tables: 0% (0 temp sorts / 247K sorts) [!!] Joins performed without indexes: 106025 [!!] Temporary tables created on disk: 49% (351K on disk / 715K total) [OK] Thread cache hit rate: 99% (249 created / 259K connections) [!!] Table cache hit rate: 15% (2K open / 13K opened) [OK] Open file limit used: 15% (3K/20K) [OK] Table locks acquired immediately: 99% (4M immediate / 4M locks) [!!] InnoDB data size / buffer pool: 39.4G/5.9G -------- Recommendations ----------------------------------------------------- General recommendations: Run OPTIMIZE TABLE to defragment tables for better performance MySQL started within last 24 hours - recommendations may be inaccurate Reduce or eliminate persistent connections to reduce connection usage Adjust your join queries to always utilize indexes Temporary table size is already large - reduce result set size Reduce your SELECT DISTINCT queries without LIMIT clauses Increase table_cache gradually to avoid file descriptor limits Variables to adjust: max_connections (> 200) wait_timeout (< 600) interactive_timeout (< 600) join_buffer_size (> 5.0M, or always use indexes with joins) table_cache (> 10000) innodb_buffer_pool_size (>= 39G) Mysql primer output -- MYSQL PERFORMANCE TUNING PRIMER -- - By: Matthew Montgomery - MySQL Version 5.5.24-9-log x86_64 Uptime = 0 days 8 hrs 20 min 50 sec Avg. qps = 478 Total Questions = 14369568 Threads Connected = 16 Warning: Server has not been running for at least 48hrs. It may not be safe to use these recommendations To find out more information on how each of these runtime variables effects performance visit: http://dev.mysql.com/doc/refman/5.5/en/server-system-variables.html Visit http://www.mysql.com/products/enterprise/advisors.html for info about MySQL's Enterprise Monitoring and Advisory Service SLOW QUERIES The slow query log is enabled. Current long_query_time = 1.000000 sec. You have 260626 out of 14369701 that take longer than 1.000000 sec. to complete Your long_query_time seems to be fine BINARY UPDATE LOG The binary update log is enabled Binlog sync is not enabled, you could loose binlog records during a server crash WORKER THREADS Current thread_cache_size = 50 Current threads_cached = 45 Current threads_per_sec = 0 Historic threads_per_sec = 0 Your thread_cache_size is fine MAX CONNECTIONS Current max_connections = 200 Current threads_connected = 11 Historic max_used_connections = 201 The number of used connections is 100% of the configured maximum. You should raise max_connections INNODB STATUS Current InnoDB index space = 214 M Current InnoDB data space = 39.40 G Current InnoDB buffer pool free = 0 % Current innodb_buffer_pool_size = 5.85 G Depending on how much space your innodb indexes take up it may be safe to increase this value to up to 2 / 3 of total system memory MEMORY USAGE Max Memory Ever Allocated : 23.46 G Configured Max Per-thread Buffers : 15.84 G Configured Max Global Buffers : 7.54 G Configured Max Memory Limit : 23.39 G Physical Memory : 31.40 G Max memory limit seem to be within acceptable norms KEY BUFFER Current MyISAM index space = 5.61 G Current key_buffer_size = 1.47 G Key cache miss rate is 1 : 5578 Key buffer free ratio = 77 % Your key_buffer_size seems to be fine QUERY CACHE Query cache is enabled Current query_cache_size = 200 M Current query_cache_used = 101 M Current query_cache_limit = 50 M Current Query cache Memory fill ratio = 50.59 % Current query_cache_min_res_unit = 4 K MySQL won't cache query results that are larger than query_cache_limit in size SORT OPERATIONS Current sort_buffer_size = 64 M Current read_rnd_buffer_size = 256 K Sort buffer seems to be fine JOINS Current join_buffer_size = 5.00 M You have had 106606 queries where a join could not use an index properly You have had 8 joins without keys that check for key usage after each row join_buffer_size >= 4 M This is not advised You should enable "log-queries-not-using-indexes" Then look for non indexed joins in the slow query log. OPEN FILES LIMIT Current open_files_limit = 20210 files The open_files_limit should typically be set to at least 2x-3x that of table_cache if you have heavy MyISAM usage. Your open_files_limit value seems to be fine TABLE CACHE Current table_open_cache = 10000 tables Current table_definition_cache = 2000 tables You have a total of 1910 tables You have 2151 open tables. The table_cache value seems to be fine TEMP TABLES Current max_heap_table_size = 2.92 G Current tmp_table_size = 2.92 G Of 366426 temp tables, 49% were created on disk Perhaps you should increase your tmp_table_size and/or max_heap_table_size to reduce the number of disk-based temporary tables Note! BLOB and TEXT columns are not allow in memory tables. If you are using these columns raising these values might not impact your ratio of on disk temp tables. TABLE SCANS Current read_buffer_size = 3 M Current table scan ratio = 2846 : 1 read_buffer_size seems to be fine TABLE LOCKING Current Lock Wait ratio = 1 : 185 You may benefit from selective use of InnoDB. If you have long running SELECT's against MyISAM tables and perform frequent updates consider setting 'low_priority_updates=1'

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  • What Wireless Router/ADSL Modem to get? N-band a must!!

    - by JJarava
    I'm looking for a Dual-N band Router OR ADSL Gateway and I'd like some recommendations. Situation: I have a 802.11b/g ADSL gateway provided by my telco, but the WIFI signal won't cover all the house (especially the living-room, so my tv-connected Mac Mini has poor to no internet access). So I'm looking to either replace the DSL modem with a N-enabled one, or to add a Router to the mix. I've had a modem+router setup for many years, and I know the advantatges (double NAT, double FW = more security) and issues (more complex to troubleshoot, two possible points of failure), so I'd rather live with a single (ADSL Gateway) device, if possible. Requirements: Dual-N Band (300 Mbs WIFI) 1 GB Ethernet ports ADSL2+ support (if it's a ADSL gateway, which would be desirable) "Best" range and speed possible Nice to have: USB port to share disks/printers on the network Media streaming I've been a long time user of Linksys, so googling around I found the WRT610N (http://www.linksysbycisco.com/US/en/products/WRT610N) for a "Pure Router" perspective, and it's one of those that Linksys styles "N++" (http://www.linksysbycisco.com/US/en/promo/Promotion-Go-Wireless?stepname=Promotion-Step-Go-Wireless-High-Performance) But I haven't been able to find similar "ADSL" gateways. I've found the WAG320N, but there is little to no info in the Linksys site (i.e., i don't know if it's Dual Band, or if it has GB ethernet) Any opinions/recommendations of other products/suggestions are more than welcome.

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  • The Server Fault Wiki of recommended practices [migrated]

    - by Avery Payne
    So I've noticed that there are several recommendations on basic practices on Server Fault, but there doesn't seem to be a cohesive view as to how those recommendations would all fit together. So I thought I would lump these together as a kind of mental exercise to see what the "ServerFault Community IT Department" would look like if it were implemented. This would give a few things: it would make a reasonable wiki (in the true wiki spirit of many contributions), it would provide several links to well-vetted practices, and it would be kind of fun to see what the amalgamation would look like. And who knows, it may even point out some interesting issues between different forms of "best practices", although I would be stunned if there was a conflict hidden in there someplace... Add your favorites from Server Fault as answers, and I'll re-edit this section with the results. Here's a few catagories to collect different ideas together. Hardware Configuration(s) Server room configuration. Server room temperature Firmware Updates and Scheduling Storage Configuration(s) Selecting a NAS box Linux: Dealing with /tmp Linux: Install apps in /var or /opt? Network Configuration(s) checking DNS health and compliance Security Practice(s) Password (General) Best Practices Password sharing methods Windows Update Updating Windows Servers that are hosts for VMs Network Service(s) User Service(s) User Naming & Deletion Upgrade Process(es) Disaster Recovery Checking Backups Documenting an outage for a post-mortem review Last Edit: 2010-02-17

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  • Tuning up a MySQL server

    - by NinjaCat
    I inherited a mysql server, and so I've started with running the MySQLTuner.pl script. I am not a MySQL expert but I can see that there is definitely a mess here. I'm not looking to go after every single thing that needs fixing and tuning, but I do want to grab the major, low hanging fruit. Total Memory on the system is: 512MB. Yes, I know it's low, but it's what we have for the time being. Here's what the script had to say: General recommendations: Run OPTIMIZE TABLE to defragment tables for better performance MySQL started within last 24 hours - recommendations may be inaccurate Enable the slow query log to troubleshoot bad queries When making adjustments, make tmp_table_size/max_heap_table_size equal Reduce your SELECT DISTINCT queries without LIMIT clauses Increase table_cache gradually to avoid file descriptor limits Your applications are not closing MySQL connections properly Variables to adjust: query_cache_limit (> 1M, or use smaller result sets) tmp_table_size (> 16M) max_heap_table_size (> 16M) table_cache (> 64) innodb_buffer_pool_size (>= 326M) For the variables that it recommends that I adjust, I don't even see most of them in the mysql.cnf file. [client] port = 3306 socket = /var/run/mysqld/mysqld.sock [mysqld_safe] socket = /var/run/mysqld/mysqld.sock nice = 0 [mysqld] innodb_buffer_pool_size = 220M innodb_flush_log_at_trx_commit = 2 innodb_file_per_table = 1 innodb_thread_concurrency = 32 skip-locking big-tables max_connections = 50 innodb_lock_wait_timeout = 600 slave_transaction_retries = 10 innodb_table_locks = 0 innodb_additional_mem_pool_size = 20M user = mysql socket = /var/run/mysqld/mysqld.sock port = 3306 basedir = /usr datadir = /var/lib/mysql tmpdir = /tmp skip-external-locking bind-address = localhost key_buffer = 16M max_allowed_packet = 16M thread_stack = 192K thread_cache_size = 4 myisam-recover = BACKUP query_cache_limit = 1M query_cache_size = 16M log_error = /var/log/mysql/error.log expire_logs_days = 10 max_binlog_size = 100M skip-locking innodb_file_per_table = 1 big-tables [mysqldump] quick quote-names max_allowed_packet = 16M [mysql] [isamchk] key_buffer = 16M !includedir /etc/mysql/conf.d/

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  • Inexpensive (used) hardware for Xen virtualization test?

    - by Jason Antman
    Virtualization is one of the areas where I could really use some experience. I also run quite a few services (web, mail, dns, etc.) out of my home. Since most of my hardware is getting a bit old (I'm running on stuff that was surplused years ago...) I decided that it's about time I start renewing some things, and also play around with virtualization a bit more. My plan is to setup a SAN box (simple iSCSI target, relatively inexpensive gigE switch), get a pair (for starters) of new servers, and start building some new stuff with Xen, specifically planning on playing with live migration and full virtualization. Does anyone have recommendations for used, older "servers" (really anything in a rack-mount form factor, I'm not too worried about things like iLO/iLOM for the test nodes) that support VT-x/AMD-V? I'm biased to HP, but it looks like they didn't make Proliants with VT-x/Vanderpool processors until G6 (for the DL360) or so, which is way out of my price range. I'm looking in the sub-$300 range (or less, if possible), used, probably Ebay. Any recommendations are greatly appreciated. Edit:And, to catch this before the comments start coming - these are personal systems. I have first-generation Proliants still in use (I got them as corporate surplus in 05, they've been running since then, and probably were running since 01 or 02 prior to being sold). I don't need anything shiny and new - I've got a bunch of old boxes, at least one complete replacement for every model in use, and that's fine for me (and easy on the wallet).

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  • Optimizing MySQL for small VPS

    - by Chris M
    I'm trying to optimize my MySQL config for a verrry small VPS. The VPS is also running NGINX/PHP-FPM and Magento; all with a limit of 250MB of RAM. This is an output of MySQL Tuner... -------- General Statistics -------------------------------------------------- [--] Skipped version check for MySQLTuner script [OK] Currently running supported MySQL version 5.1.41-3ubuntu12.8 [OK] Operating on 64-bit architecture -------- Storage Engine Statistics ------------------------------------------- [--] Status: -Archive -BDB -Federated +InnoDB -ISAM -NDBCluster [--] Data in MyISAM tables: 1M (Tables: 14) [--] Data in InnoDB tables: 29M (Tables: 301) [--] Data in MEMORY tables: 1M (Tables: 17) [!!] Total fragmented tables: 301 -------- Security Recommendations ------------------------------------------- [OK] All database users have passwords assigned -------- Performance Metrics ------------------------------------------------- [--] Up for: 2d 11h 14m 58s (1M q [8.038 qps], 33K conn, TX: 2B, RX: 618M) [--] Reads / Writes: 83% / 17% [--] Total buffers: 122.0M global + 8.6M per thread (100 max threads) [!!] Maximum possible memory usage: 978.2M (404% of installed RAM) [OK] Slow queries: 0% (37/1M) [OK] Highest usage of available connections: 6% (6/100) [OK] Key buffer size / total MyISAM indexes: 32.0M/282.0K [OK] Key buffer hit rate: 99.7% (358K cached / 1K reads) [OK] Query cache efficiency: 83.4% (1M cached / 1M selects) [!!] Query cache prunes per day: 48301 [OK] Sorts requiring temporary tables: 0% (0 temp sorts / 144K sorts) [OK] Temporary tables created on disk: 13% (27K on disk / 203K total) [OK] Thread cache hit rate: 99% (6 created / 33K connections) [!!] Table cache hit rate: 0% (32 open / 51K opened) [OK] Open file limit used: 1% (20/1K) [OK] Table locks acquired immediately: 99% (1M immediate / 1M locks) [!!] InnoDB data size / buffer pool: 29.2M/8.0M -------- Recommendations ----------------------------------------------------- General recommendations: Run OPTIMIZE TABLE to defragment tables for better performance Reduce your overall MySQL memory footprint for system stability Enable the slow query log to troubleshoot bad queries Increase table_cache gradually to avoid file descriptor limits Variables to adjust: *** MySQL's maximum memory usage is dangerously high *** *** Add RAM before increasing MySQL buffer variables *** query_cache_size (> 64M) table_cache (> 32) innodb_buffer_pool_size (>= 29M) and this is the config. # # The MySQL database server configuration file. # # You can copy this to one of: # - "/etc/mysql/my.cnf" to set global options, # - "~/.my.cnf" to set user-specific options. # # One can use all long options that the program supports. # Run program with --help to get a list of available options and with # --print-defaults to see which it would actually understand and use. # # For explanations see # http://dev.mysql.com/doc/mysql/en/server-system-variables.html # This will be passed to all mysql clients # It has been reported that passwords should be enclosed with ticks/quotes # escpecially if they contain "#" chars... # Remember to edit /etc/mysql/debian.cnf when changing the socket location. [client] port = 3306 socket = /var/run/mysqld/mysqld.sock # Here is entries for some specific programs # The following values assume you have at least 32M ram # This was formally known as [safe_mysqld]. Both versions are currently parsed. [mysqld_safe] socket = /var/run/mysqld/mysqld.sock nice = 0 [mysqld] # # * Basic Settings # # # * IMPORTANT # If you make changes to these settings and your system uses apparmor, you may # also need to also adjust /etc/apparmor.d/usr.sbin.mysqld. # user = mysql socket = /var/run/mysqld/mysqld.sock port = 3306 basedir = /usr datadir = /var/lib/mysql tmpdir = /tmp skip-external-locking # # Instead of skip-networking the default is now to listen only on # localhost which is more compatible and is not less secure. bind-address = 127.0.0.1 # # * Fine Tuning # key_buffer = 32M max_allowed_packet = 16M thread_stack = 192K thread_cache_size = 8 sort_buffer_size = 4M read_buffer_size = 4M myisam_sort_buffer_size = 16M # This replaces the startup script and checks MyISAM tables if needed # the first time they are touched myisam-recover = BACKUP max_connections = 100 table_cache = 32 tmp_table_size = 128M #thread_concurrency = 10 # # * Query Cache Configuration # #query_cache_limit = 1M query_cache_type = 1 query_cache_size = 64M # # * Logging and Replication # # Both location gets rotated by the cronjob. # Be aware that this log type is a performance killer. # As of 5.1 you can enable the log at runtime! #general_log_file = /var/log/mysql/mysql.log #general_log = 1 log_error = /var/log/mysql/error.log # Here you can see queries with especially long duration #log_slow_queries = /var/log/mysql/mysql-slow.log #long_query_time = 2 #log-queries-not-using-indexes # # The following can be used as easy to replay backup logs or for replication. # note: if you are setting up a replication slave, see README.Debian about # other settings you may need to change. #server-id = 1 #log_bin = /var/log/mysql/mysql-bin.log expire_logs_days = 10 max_binlog_size = 100M #binlog_do_db = include_database_name #binlog_ignore_db = include_database_name # # * InnoDB # # InnoDB is enabled by default with a 10MB datafile in /var/lib/mysql/. # Read the manual for more InnoDB related options. There are many! # # * Security Features # # Read the manual, too, if you want chroot! # chroot = /var/lib/mysql/ # # For generating SSL certificates I recommend the OpenSSL GUI "tinyca". # # ssl-ca=/etc/mysql/cacert.pem # ssl-cert=/etc/mysql/server-cert.pem # ssl-key=/etc/mysql/server-key.pem [mysqldump] quick quote-names max_allowed_packet = 16M [mysql] #no-auto-rehash # faster start of mysql but no tab completition [isamchk] key_buffer = 16M # # * IMPORTANT: Additional settings that can override those from this file! # The files must end with '.cnf', otherwise they'll be ignored. # !includedir /etc/mysql/conf.d/ The site contains 1 wordpress site,so lots of MYISAM but mostly static content as its not changing all that often (A wordpress cache plugin deals with this). And the Magento Site which consists of a lot of InnoDB tables, some MyISAM and some INMEMORY. The "read" side seems to be running pretty well with a mass of optimizations I've used on Magento, the NGINX setup and PHP-FPM + XCACHE. I'd love to have a kick in the right direction with the MySQL config so I'm not blindly altering it based on the MySQLTuner without understanding what I'm changing. Thanks

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  • Server Memory with Magento

    - by Mohamed Elgharabawy
    I have a cloud server with the following specifications: 2vCPUs 4G RAM 160GB Disk Space Network 400Mb/s System Image: Ubuntu 12.04 LTS I am only running Magento CE 1.7.0.2 on this server. Nothing else. Usually, the server has a loading time of 4-5 seconds. Recently, this has dropped to over 30 seconds and sometimes the server just goes away and I get HTTP error reports to my email stating that HTTP requests took more than 20000ms. Running top command and sorting them returns the following: top - 15:29:07 up 3:40, 1 user, load average: 28.59, 25.95, 22.91 Tasks: 112 total, 30 running, 82 sleeping, 0 stopped, 0 zombie Cpu(s): 90.2%us, 9.3%sy, 0.0%ni, 0.0%id, 0.0%wa, 0.0%hi, 0.3%si, 0.2%st PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 31901 www-data 20 0 360m 71m 5840 R 7 1.8 1:39.51 apache2 32084 www-data 20 0 362m 72m 5548 R 7 1.8 1:31.56 apache2 32089 www-data 20 0 348m 59m 5660 R 7 1.5 1:41.74 apache2 32295 www-data 20 0 343m 54m 5532 R 7 1.4 2:00.78 apache2 32303 www-data 20 0 354m 65m 5260 R 7 1.6 1:38.76 apache2 32304 www-data 20 0 346m 56m 5544 R 7 1.4 1:41.26 apache2 32305 www-data 20 0 348m 59m 5640 R 7 1.5 1:50.11 apache2 32291 www-data 20 0 358m 69m 5256 R 6 1.7 1:44.26 apache2 32517 www-data 20 0 345m 56m 5532 R 6 1.4 1:45.56 apache2 30473 www-data 20 0 355m 66m 5680 R 6 1.7 2:00.05 apache2 32093 www-data 20 0 352m 63m 5848 R 6 1.6 1:53.23 apache2 32302 www-data 20 0 345m 56m 5512 R 6 1.4 1:55.87 apache2 32433 www-data 20 0 346m 57m 5500 S 6 1.4 1:31.58 apache2 32638 www-data 20 0 354m 65m 5508 R 6 1.6 1:36.59 apache2 32230 www-data 20 0 347m 57m 5524 R 6 1.4 1:33.96 apache2 32231 www-data 20 0 355m 66m 5512 R 6 1.7 1:37.47 apache2 32233 www-data 20 0 354m 64m 6032 R 6 1.6 1:59.74 apache2 32300 www-data 20 0 355m 66m 5672 R 6 1.7 1:43.76 apache2 32510 www-data 20 0 347m 58m 5512 R 6 1.5 1:42.54 apache2 32521 www-data 20 0 348m 59m 5508 R 6 1.5 1:47.99 apache2 32639 www-data 20 0 344m 55m 5512 R 6 1.4 1:34.25 apache2 32083 www-data 20 0 345m 56m 5696 R 5 1.4 1:59.42 apache2 32085 www-data 20 0 347m 58m 5692 R 5 1.5 1:42.29 apache2 32293 www-data 20 0 353m 64m 5676 R 5 1.6 1:52.73 apache2 32301 www-data 20 0 348m 59m 5564 R 5 1.5 1:49.63 apache2 32528 www-data 20 0 351m 62m 5520 R 5 1.6 1:36.11 apache2 31523 mysql 20 0 3460m 576m 8288 S 5 14.4 2:06.91 mysqld 32002 www-data 20 0 345m 55m 5512 R 5 1.4 2:01.88 apache2 32080 www-data 20 0 357m 68m 5512 S 5 1.7 1:31.30 apache2 32163 www-data 20 0 347m 58m 5512 S 5 1.5 1:58.68 apache2 32509 www-data 20 0 345m 56m 5504 R 5 1.4 1:49.54 apache2 32306 www-data 20 0 358m 68m 5504 S 4 1.7 1:53.29 apache2 32165 www-data 20 0 344m 55m 5524 S 4 1.4 1:40.71 apache2 32640 www-data 20 0 345m 56m 5528 R 4 1.4 1:36.49 apache2 31888 www-data 20 0 359m 70m 5664 R 4 1.8 1:57.07 apache2 32511 www-data 20 0 357m 67m 5512 S 3 1.7 1:47.00 apache2 32054 www-data 20 0 357m 68m 5660 S 2 1.7 1:53.10 apache2 1 root 20 0 24452 2276 1232 S 0 0.1 0:01.58 init Moreover, running free -m returns the following: total used free shared buffers cached Mem: 4003 3919 83 0 118 901 -/+ buffers/cache: 2899 1103 Swap: 0 0 0 To investigate this further, I have installed apache buddy, it recommeneded that I need to reduce the maxclient connections. Which I did. I also installed MysqlTuner and it suggests that I need to set my innodb_buffer_pool_size to = 3.0G. However, I cannot do that, since the whole memory is 4G. Here is the output from apache buddy: ### GENERAL REPORT ### Settings considered for this report: Your server's physical RAM: 4003MB Apache's MaxClients directive: 40 Apache MPM Model: prefork Largest Apache process (by memory): 73.77MB [ OK ] Your MaxClients setting is within an acceptable range. Max potential memory usage: 2950.8 MB Percentage of RAM allocated to Apache 73.72 % And this is the output of MySQLTuner: -------- Performance Metrics ------------------------------------------------- [--] Up for: 47m 22s (675K q [237.552 qps], 12K conn, TX: 1B, RX: 300M) [--] Reads / Writes: 45% / 55% [--] Total buffers: 2.1G global + 2.7M per thread (151 max threads) [OK] Maximum possible memory usage: 2.5G (64% of installed RAM) [OK] Slow queries: 0% (0/675K) [OK] Highest usage of available connections: 26% (40/151) [OK] Key buffer size / total MyISAM indexes: 36.0M/18.7M [OK] Key buffer hit rate: 100.0% (245K cached / 105 reads) [OK] Query cache efficiency: 92.5% (500K cached / 541K selects) [!!] Query cache prunes per day: 302886 [OK] Sorts requiring temporary tables: 0% (1 temp sorts / 15K sorts) [!!] Joins performed without indexes: 12135 [OK] Temporary tables created on disk: 25% (8K on disk / 32K total) [OK] Thread cache hit rate: 90% (1K created / 12K connections) [!!] Table cache hit rate: 17% (400 open / 2K opened) [OK] Open file limit used: 12% (123/1K) [OK] Table locks acquired immediately: 100% (196K immediate / 196K locks) [!!] InnoDB buffer pool / data size: 2.0G/3.5G [OK] InnoDB log waits: 0 -------- Recommendations ----------------------------------------------------- General recommendations: Run OPTIMIZE TABLE to defragment tables for better performance MySQL started within last 24 hours - recommendations may be inaccurate Enable the slow query log to troubleshoot bad queries Adjust your join queries to always utilize indexes Increase table_cache gradually to avoid file descriptor limits Read this before increasing table_cache over 64: http://bit.ly/1mi7c4C Variables to adjust: query_cache_size ( 64M) join_buffer_size ( 128.0K, or always use indexes with joins) table_cache ( 400) innodb_buffer_pool_size (= 3G) Last but not least, the server still has more than 60% of free disk space. Now, based on the above, I have few questions: Are these numbers normal? Do they make sense? Do I need to upgrade the server? If I don't need to upgrade and my configuration is not correct, how do I optimize it?

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  • Oracle Products Reflect Key Trends Shaping Enterprise 2.0

    - by kellsey.ruppel(at)oracle.com
    Following up on his predictions for 2011, we asked Enterprise 2.0 veteran Andy MacMillan to map out the ways Oracle solutions are at the forefront of industry trends--and how Oracle customers can benefit in the coming year. 1. Increase organizational awareness | Oracle WebCenter Suite Oracle WebCenter Suite provides a unique set of capabilities to drive organizational awareness. In particular, the expansive activity graph connects users directly to key enterprise applications, activities, and interests. In this way, applicable and critical business information is automatically and immediately visible--in the context of key tasks--via real-time dashboards and comprehensive reporting. Oracle WebCenter Suite also integrates key E2.0 services, such as blogs, wikis, and RSS feeds, into critical business processes, including back-office systems of records such as ERP and CRM systems. 2. Drive online customer engagement | Oracle Real-Time Decisions With more and more business being conducted on the Web, driving increased online customer engagement becomes a critical key to success. This effort is usually spearheaded by an increasingly important executive role, the Head of Online, who usually reports directly to the CMO. To help manage the Web experience online, Oracle solutions are driving a new kind of intelligent social commerce by combining Oracle Universal Content Management, Oracle WebCenter Services, and Oracle Real-Time Decisions with leading e-commerce and product recommendations. Oracle Real-Time Decisions provides multichannel recommendations for content, products, and services--including seamless integration across Web, mobile, and social channels. The result: happier customers, increased customer acquisition and retention, and improved critical success metrics such as shopping cart abandonment. 3. Easily build composite applications | Oracle Application Development Framework Thanks to the shared user experience strategy across Oracle Fusion Middleware, Oracle Fusion Applications and many other Oracle Applications, customers can easily create real, customer-specific composite applications using Oracle WebCenter Suite and Oracle Application Development Framework. Oracle Application Development Framework components provide modular user interface components that can build rich, social composite applications. In addition, a broad set of components spanning BPM, SOA, ECM, and beyond can be quickly and easily incorporated into composite applications. 4. Integrate records management into a global content platform | Oracle Enterprise Content Management 11g Oracle Enterprise Content Management 11g provides leading records management capabilities as part of a unified ECM platform for managing records, documents, Web content, digital assets, enterprise imaging, and application imaging. This unique strategy provides comprehensive records management in a consistent, cost-effective way, and enables organizations to consolidate ECM repositories and connect ECM to critical business applications. 5. Achieve ECM at extreme scale | Oracle WebLogic Server and Oracle Exadata To support the high-performance demands of a unified and rationalized content platform, Oracle has pioneered highly scalable and high-performing ECM infrastructures. Two innovations in particular helped make this happen. The core ECM platform itself moved to an Enterprise Java architecture, so organizations can now use Oracle WebLogic Server for enhanced scalability and manageability. Oracle Enterprise Content Management 11g can leverage Oracle Exadata for extreme performance and scale. Likewise, Oracle Exalogic--Oracle's foundation for cloud computing--enables extreme performance for processor-intensive capabilities such as content conversion or dynamic Web page delivery. Learn more about Oracle's Enterprise 2.0 solutions.

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  • Hey Retailers, Are You Ready For The Holiday Season?

    - by Jeri Kelley
    With online holiday spending reaching $35.3 billion in 2011 and American shoppers spending just under $750 on average on their holiday purchases this year, how ready is your business for the 2012 holiday season?   ?? Today’s shoppers do not take their purchases lightly.  They are more connected, interact with more resources to make decisions, diligently compare products and services, seek out the best deals, and ask for input from friends and family.   This holiday season, as consumers browse for apparel, tablets, toys, and much more, they will be bombarded with retailer communication - from emails and commercials to countless search engine results and social recommendations.  With a flurry of activity coming at consumers from every channel and competitor, your success this year will rely on communicating a consistent, personalized message no matter where your customers are shopping.  Here are a few ideas to help with your commerce strategy this holiday season: CONSISTENCY COUNTS FOR MULTICHANNEL SHOPPERS??According to a November 2011 study commissioned by Oracle, “Channel Commerce 2011: The Consumer View,” 54% of consumers in the U.S. and Canada regularly employ two or more channels before they make a purchase.  While each channel has its own unique benefit, user profile, and purpose, it’s critical that your shoppers have a consistent core experience wherever they’re looking for information or making a purchase.  Be sure consumers can consistently search and browse the same product information and receive the same promotions online, on their mobile devices, and in-store.? USE YOUR CUSTOMER’S CONTEXT TO SURFACE RELEVANT CONTENTYour Web site is likely the hub of your holiday activity.  According to a Monetate infographic, 39% of shoppers will visit your Web site directly to find out about the best holiday deals.   Use everything you know about your customers from past purchase data to browsing history to provide a relevant experience at every click, and assemble content in a context that entices shoppers to buy online, or influences an offline purchase.? TAKE ADVANTAGE OF MOBILE BEHAVIOR?Having a mobile program is no longer a choice.   Armed with smartphones and tablets, consumers now have access to more and more product information and can compare products and prices from anywhere.  In fact, approximately 52% of smartphone users will use their device to research products, redeem coupons and use apps to assist in their holiday gift purchase.  At a minimum, be sure your mobile environment has store information, consistent pricing and promotions, and simple checkout capabilities. ARM IN-STORE ASSOCIATES WITH TABLETS?According to RISNews.com, 31% of retailers plan to begin testing tablets in stores in 2012, 22% have already begun such testing and 6% had fully deployed tablets within stores.   Take advantage of this compelling sales tool to get shoppers interacting with videos, user reviews, how-to guides, side-by-side product comparisons, and specs.  Automatically trigger upsell and cross sell suggestions for store associates to recommend for each product or category, build in alerts for promotions, and allow associates to place orders and check inventory from their tablet.  ? WISDOM OF THE CROWDS IS GOOD, BUT WISDOM FROM FRIENDS IS BETTER?Shoppers who grapple with options are looking for recommendations; they’d rather get advice from friends, and they’re more likely to spend more while doing so.    In fact, according to an infographic by Mr. Youth, 66% of social media users made a purchase on Black Friday or Cyber Monday as a direct result of social media interactions with brands or family.   This holiday season, be sure you are leveraging your social channels from Facebook to Pinterest to drive consistent promotions and help your brand to become part of the conversation. So, are you ready for the holidays this year?  

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  • Social Search: Looking for Love

    - by Mike Stiles
    For marketers and enterprise executives who have placed a higher priority on and allocated bigger budgets to search over social, it might be time to notice yet another shift that’s well underway. Social is search. Search marketing was always more of an internal slam-dunk than other digital initiatives. Even a C-suite that understood little about the new technology world knew it’s a good thing when people are able to find you. Google was the new Yellow Pages. Only with Google, you could get your listing first without naming yourself “AAAA Plumbing.” There were wizards out there who could give your business prominence in front of people who were specifically looking for what you offered. Other search giants like Bing also came along to offer such ideal matchmaking possibilities. But what if the consumer isn’t using a search engine to find what they’re looking for? And what if the search engines started altering their algorithms so that search placement manipulation was more difficult? Both of those things have started to happen. Experian Hitwise’s numbers show that visits to the major search engines in the UK dropped 100 million through August. Search engines are far from dead, or even challenged. But more and more, the public is discovering the sites and brands they need through advice they get via social, not search. You’ll find the worlds of social and search increasingly co-mingling as well. Search behemoths Google and Bing are including Facebook and Google+ into their engines. Meanwhile, Facebook and Twitter have done some integration of global web search into their platforms. So what makes social such a worthwhile search entity for brands? First and foremost, the consumer has demonstrated a behavior of acting on recommendations from social connections. A cry in the wilderness like, “Anybody know any good catering companies?” will usually yield a link (and an endorsement) from a friend such as “Yeah, check out Just-Cheese-Balls Catering.” There’s no such human-driven force/influence behind the big search engines. Facebook’s Mark Zuckerberg and others call it “Friend Mining.” It is, in essence, searching for answers from friends’ experiences as opposed to faceless code. And Facebook has all of those friends’ experiences already stored as data. eMarketer says search in an $18 billion business, and investors are really into it. So no shock Facebook’s ready to leverage their social graph into relevant search. What do you do about all this as a brand? For one thing, it’s going to lead to some interesting paid marketing opportunities around the corner, including Sponsored Stories bought against certain queries, inserting deals into search results, capitalizing on social search results on mobile, etc. Apart from that, it might be time to stop mentally separating social and search in your strategic planning and budgeting. Courting your fans on social will cumulatively add up to more valuable, personally endorsed recommendations for your company when a consumer conducts a search on social. Fail to foster those relationships, fail to engage, fail to provide knock-em-dead customer service, fail to wow them with your actual products and services…and you’ll wind up with the visibility you deserve in social search results.

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  • Scalable / Parallel Large Graph Analysis Library?

    - by Joel Hoff
    I am looking for good recommendations for scalable and/or parallel large graph analysis libraries in various languages. The problems I am working on involve significant computational analysis of graphs/networks with 1-100 million nodes and 10 million to 1+ billion edges. The largest SMP computer I am using has 256 GB memory, but I also have access to an HPC cluster with 1000 cores, 2 TB aggregate memory, and MPI for communication. I am primarily looking for scalable, high-performance graph libraries that could be used in either single or multi-threaded scenarios, but parallel analysis libraries based on MPI or a similar protocol for communication and/or distributed memory are also of interest for high-end problems. Target programming languages include C++, C, Java, and Python. My research to-date has come up with the following possible solutions for these languages: C++ -- The most viable solutions appear to be the Boost Graph Library and Parallel Boost Graph Library. I have looked briefly at MTGL, but it is currently slanted more toward massively multithreaded hardware architectures like the Cray XMT. C - igraph and SNAP (Small-world Network Analysis and Partitioning); latter uses OpenMP for parallelism on SMP systems. Java - I have found no parallel libraries here yet, but JGraphT and perhaps JUNG are leading contenders in the non-parallel space. Python - igraph and NetworkX look like the most solid options, though neither is parallel. There used to be Python bindings for BGL, but these are now unsupported; last release in 2005 looks stale now. Other topics here on SO that I've looked at have discussed graph libraries in C++, Java, Python, and other languages. However, none of these topics focused significantly on scalability. Does anyone have recommendations they can offer based on experience with any of the above or other library packages when applied to large graph analysis problems? Performance, scalability, and code stability/maturity are my primary concerns. Most of the specialized algorithms will be developed by my team with the exception of any graph-oriented parallel communication or distributed memory frameworks (where the graph state is distributed across a cluster).

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  • Movies recommendation engine conceptual database design

    - by Supyxy
    I am working at an movie recommendations engine and i'm facing a DB design issue. My actual database looks like this: MOVIES [ID,TITLE] KEYWORDS_TABLE [ID,KEY_ID] - where ID is Foreign Key for MOVIES.id and KEY_ID is a key for a text keywords table This is not the entire DB, but i showed here what's important for my problem. I have about 50,000 movies and about 1,3 milion keywords correlations, and basically my algorithm consists in extracting all the who have the same keywords with a given movie, then ordering them by the number of keywords correlations. For example i looked for a movie similar to 'Cast away' and it returned 'Six days and six nights' because it had the most keywords correlations (4 keywords): Island Airplane crash Stranded Pilot The algorithm is based on more factors, but this one is the most important and the most difficult for the approach. Basically what i do now is getting all the movies that have at least one keyword similar to the given movie and then ordering them by other factors which are not important for a moment. There wouldn't be any problem if there weren't so many records, a query lasts in many cases up to 10-20 seconds and some of them return even over 5000 movies. Someone already helped me on here (thanks Mark Byers) with optimizing the query but that's not enough because it takes too longer SELECT DISTINCT M.title FROM keywords_table K1 JOIN keywords_table K2 ON K2.key_id = K1.key_id JOIN movies M ON K2.id = M.id WHERE K1.id = 4 So i thought it would be better if i pre-made those lists with movies recommendations for each movie, but i'm not sure how to design the tables.. whatever is it a good idea or how would you take this approach?

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  • error detection/correction/recovery in serial protocols

    - by Jason S
    I have some designing to do for a serial protocol and am running into some questions that I figure must have been considered elsewhere. So I'm wondering if there are some recommendations for best practices in designing serial protocols. (Please either state a fact that is easily verifiable, or cite a reputable source if you make a claim.) General recommendations for websites/books are also welcome. In particular I have to deal with issues like parsing a stream of bytes into packets verifying a packet is correct (easy with a CRC, for instance) identifying reasonable types of errors that can occur (e.g. in a point-to-point serial stream, sporadic single bit errors, and dropped series of bytes, are both likely, but extra phantom bytes are unlikely; whereas with a record stored in flash memory or on a disk drive the types of errors that predominate are different) error correction or recovery (if I detect an error in a packet, can I correct it? If not, can I resync to the boundary of the next packet?) how to make variable-length packets robust to error correction / recovery. Any suggestions?

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  • Structuring input of data for localStorage

    - by WmasterJ
    It is nice when there isn't a DB to maintain and users to authenticate. My professor has asked me to convert a recent research project of his that uses Bespin and calculates errors made by users in a code editor as part of his research. The goal is to convert from MySQL to using HTML5 localStorage completely. Doesn't seem so hard to do, even though digging in his code might take some time. Question: I need to store files and state (last placement of cursor and active file). I have already done so by implementing the recommendations in another stackoverflow thread. But would like your input considering how to structure the content to use. My current solution Hashmap like solution with javascript objects: files = {}; // later, saving files[fileName] = data; And then storing in localStorage using some recommendations localStorage.setObject(files): Currently I'm also considering using some type of numeric id. So that names can be changed without any hassle renaming the key in the hashmap. What is your opinion on the way it is solved and would you do it any differently?

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  • Mercurial repository usage with binary files for building setup files

    - by Ryan
    I have an existing Mercurial repository for a C++ application in a small corporate environment. I asked a co-worker to add the setup script to the repository and he added all of the dependency binaries, PDFs, and executable to the repository under an Install directory. I dislike having the binaries and dependencies in the same repository, but I'd like recommendations on best practices. Here are the options I am considering: Create a separate repository for the Installer and related files Create a subrepository for the Installer and related files Use a (yet to be identified) build dependency manager I am concerned with using a subrepository with Mercurial based on what I've read so far and the (apparently) incomplete implementation. I would like to get a project dependency system, e.g. Ivy, but I don't know all of the options and haven't had time yet to try out any options. I thought I'd use TortoiseHg as a basis, and it does not have the TortoiseHg binaries in the repository although it does have some binaries such as kdiff3.exe. Instead it uses setup.py to clone multiple repositories and build the apps. This seems reasonable for OSS, but not so much for corporate environments. Recommendations?

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  • Best method to search hierarchical data

    - by WDuffy
    I'm looking at building a facility which allows querying for data with hierarchical filtering. I have a few ideas how I'm going to go about it but was wondering if there are any recommendations or suggestions that might be more efficient. As an example imagine that a user is searching for a job. The job areas would be as follows. 1: Scotland 2: --- West Central 3: ------ Glasgow 4: ------ Etc 5: --- North East 6: ------ Ayrshire 7: ------ Etc A user can search specific (i.e. Glasgow) or in a larger area (i.e. Scotland). The two approaches I am considering are: keep a note of children in the database for each record (i.e. cat 1 would have 2, 3, 4 in its children field) and query against that record with a SELECT * FROM Jobs WHERE Category IN Areas.childrenField. Use a recursive function to find all results who have a relation to the selected area. The problems I see from both are: Holding this data in the db will mean having to keep track of all changes to structure. Recursion is slow and inefficent. Any ideas, suggestion or recommendations on the best approach? I'm using C# ASP.NET with MSSQL 2005 DB.

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  • Suitable data structures for saving files in localStorage (HTML5) ?

    - by WmasterJ
    It is nice when there isn't a DB to maintain and users to authenticate. My professor has asked me to convert a recent research project of his that uses Bespin and calculates errors made by users in a code editor as part of his research. The goal is to convert from MySQL to using HTML5 localStorage completely. Doesn't seem so hard to do, even though digging in his code might take some time. Question: I need to store files and state (last placement of cursor and active file). I have already done so by implementing the recommendations in another stackoverflow thread. But would like your input considering how to structure the content to use. My current solution Hashmap like solution with javascript objects: files = {}; // later, saving files[fileName] = data; And then storing in localStorage using some recommendations localStorage.setObject("files", files); // Note that setObject(key, data) does not exist but is added // using Storage.prototype.setObject = function() {... Currently I'm also considering using some type of numeric id. So that names can be changed without any hassle renaming the key in the hashmap. What is your opinion on the way it is solved and would you do it any differently?

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  • Best method to search heriarachal data

    - by WDuffy
    I'm looking at building a facility which allows querying for data with hierarchical filtering. I have a few ideas how I'm going to go about it but was wondering if there are any recommendations or suggestions that might be more efficient. As an example imagine that a user is searching for a job. The job areas would be as follows. 1: Scotland 2: --- West Central 3: ------ Glasgow 4: ------ Etc 5: --- North East 6: ------ Ayrshire 7: ------ Etc A user can search specific (ie Glasgow) or in a larger area (ie Scotland). The two approaches I am considering are 1: keep a note of children in the database for each record (ie cat 1 would have 2, 3, 4 in its children field) and query against that record with a SELECT * FROM Jobs WHERE Category IN Areas.childrenField. 2: Use a recursive function to find all results who have a relation to the selected area The problems I see from both are 1: holding this data in the db will mean having to keep track of all changes to structure 2: Recursion is slow and inefficent Any ideas, suggestion or recommendations on the best approach? I'm using C# ASP.NET with MSSQL 2005 DB.

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