尚硅谷大数据技术-数据湖Hudi视频教程-笔记03【Hudi集成Spark】

news2024/9/22 3:36:39

大数据新风口:Hudi数据湖(尚硅谷&Apache Hudi联合出品)

  1. B站直达:https://www.bilibili.com/video/BV1ue4y1i7na  尚硅谷数据湖Hudi视频教程
  2. 百度网盘:https://pan.baidu.com/s/1NkPku5Pp-l0gfgoo63hR-Q?pwd=yyds
  3. 阿里云盘:https://www.aliyundrive.com/s/uMCmjb8nGaC(教程配套资料请从百度网盘下载)

  1. 尚硅谷大数据技术-数据湖Hudi视频教程-笔记01【Hudi概述、Hudi编译安装】

  2. 尚硅谷大数据技术-数据湖Hudi视频教程-笔记02【Hudi核心概念(基本概念、数据写、数据读)】

  3. 尚硅谷大数据技术-数据湖Hudi视频教程-笔记03【Hudi集成Spark】

  4. 尚硅谷大数据技术-数据湖Hudi视频教程-笔记04【Hudi集成Flink】

  5. 尚硅谷大数据技术-数据湖Hudi视频教程-笔记05【Hudi集成Hive】

目录

第4章 集成 Spark

026

027

028

029

030

031


第4章 集成 Spark

026

第4章 集成 Spark

4.1 环境准备

4.1.1 安装Spark

4.1.2 启动Hadoop(略)

4.2 spark-shell 方式

4.2.1 启动 spark-shell

1)启动命令

[atguigu@node001 ~]$ spark-shell \
>   --conf 'spark.serializer=org.apache.spark.serializer.KryoSerializer' \
>   --conf 'spark.sql.catalog.spark_catalog=org.apache.spark.sql.hudi.catalog.HoodieCatalog' \
>   --conf 'spark.sql.extensions=org.apache.spark.sql.hudi.HoodieSparkSessionExtension'

Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
18760 [main] WARN  org.apache.hadoop.util.NativeCodeLoader  - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Spark context Web UI available at http://node001:4040
Spark context available as 'sc' (master = local[*], app id = local-1704790850201).
Spark session available as 'spark'.
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 3.2.2
      /_/
         
Using Scala version 2.12.15 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_212)
Type in expressions to have them evaluated.
Type :help for more information.

scala> 

027

4.2.1 启动 spark-shell

2)设置表名,基本路径和数据生成器

scala> import org.apache.hudi.QuickstartUtils._
import org.apache.hudi.QuickstartUtils._

scala> import scala.collection.JavaConversions._
import scala.collection.JavaConversions._

scala> import org.apache.spark.sql.SaveMode._
import org.apache.spark.sql.SaveMode._

scala> import org.apache.hudi.DataSourceReadOptions._
import org.apache.hudi.DataSourceReadOptions._

scala> import org.apache.hudi.DataSourceWriteOptions._
import org.apache.hudi.DataSourceWriteOptions._

scala> import org.apache.hudi.config.HoodieWriteConfig._
import org.apache.hudi.config.HoodieWriteConfig._

scala> 

scala> val tableName = "hudi_trips_cow"
tableName: String = hudi_trips_cow

scala> val basePath = "file:///tmp/hudi_trips_cow"
basePath: String = file:///tmp/hudi_trips_cow

scala> val dataGen = new DataGenerator
dataGen: org.apache.hudi.QuickstartUtils.DataGenerator = org.apache.hudi.QuickstartUtils$DataGenerator@66e6b022

scala> 

scala> 

scala> val inserts = convertToStringList(dataGen.generateInserts(10))
inserts: java.util.List[String] = [{"ts": 1704209002713, "uuid": "58f04a7a-6d32-42a6-8915-dfc00ae845fc", "rider": "rider-213", "driver": "driver-213", "begin_lat": 0.4726905879569653, "begin_lon": 0.46157858450465483, "end_lat": 0.754803407008858, "end_lon": 0.9671159942018241, "fare": 34.158284716382845, "partitionpath": "americas/brazil/sao_paulo"}, {"ts": 1704623138251, "uuid": "d2c871b0-e98e-44ee-815b-09fbcc5771bb", "rider": "rider-213", "driver": "driver-213", "begin_lat": 0.6100070562136587, "begin_lon": 0.8779402295427752, "end_lat": 0.3407870505929602, "end_lon": 0.5030798142293655, "fare": 43.4923811219014, "partitionpath": "americas/brazil/sao_paulo"}, {"ts": 1704362707376, "uuid": "74e4699e-3644-477e-9d12-bf83a67c59c1", "rider": "rider-213", "driver"...

scala> val df = spark.read.json(spark.sparkContext.parallelize(inserts, 2))
warning: one deprecation (since 2.12.0)
warning: one deprecation (since 2.2.0)
warning: two deprecations in total; for details, enable `:setting -deprecation' or `:replay -deprecation'
df: org.apache.spark.sql.DataFrame = [begin_lat: double, begin_lon: double ... 8 more fields]

scala> df.write.format("hudi").
     |   options(getQuickstartWriteConfigs).
     |   option(PRECOMBINE_FIELD_OPT_KEY, "ts").
     |   option(RECORDKEY_FIELD_OPT_KEY, "uuid").
     |   option(PARTITIONPATH_FIELD_OPT_KEY, "partitionpath").
     |   option(TABLE_NAME, tableName).
     |   mode(Overwrite).
     |   save(basePath)
warning: one deprecation; for details, enable `:setting -deprecation' or `:replay -deprecation'
7744528 [main] WARN  org.apache.hudi.common.config.DFSPropertiesConfiguration  - Cannot find HUDI_CONF_DIR, please set it as the dir of hudi-defaults.conf
7744558 [main] WARN  org.apache.hudi.common.config.DFSPropertiesConfiguration  - Properties file file:/etc/hudi/conf/hudi-defaults.conf not found. Ignoring to load props file
7747037 [main] WARN  org.apache.hudi.metadata.HoodieBackedTableMetadata  - Metadata table was not found at path file:///tmp/hudi_trips_cow/.hoodie/metadata
                                                                                
scala> 

028

4.2.3 查询数据

scala> val tripsSnapshotDF = spark.
     |   read.
     |   format("hudi").
     |   load(basePath)
tripsSnapshotDF: org.apache.spark.sql.DataFrame = [_hoodie_commit_time: string, _hoodie_commit_seqno: string ... 13 more fields]

scala> tripsSnapshotDF.createOrReplaceTempView("hudi_trips_snapshot")

scala> 

scala> spark.sql("select fare, begin_lon, begin_lat, ts from  hudi_trips_snapshot where fare > 20.0").show()
+------------------+-------------------+-------------------+-------------+
|              fare|          begin_lon|          begin_lat|           ts|
+------------------+-------------------+-------------------+-------------+
| 33.92216483948643| 0.9694586417848392| 0.1856488085068272|1704256809374|
| 64.27696295884016| 0.4923479652912024| 0.5731835407930634|1704362707376|
| 93.56018115236618|0.14285051259466197|0.21624150367601136|1704216687193|
| 27.79478688582596| 0.6273212202489661|0.11488393157088261|1704494741512|
|  43.4923811219014| 0.8779402295427752| 0.6100070562136587|1704623138251|
| 66.62084366450246|0.03844104444445928| 0.0750588760043035|1704568660989|
|34.158284716382845|0.46157858450465483| 0.4726905879569653|1704209002713|
| 41.06290929046368| 0.8192868687714224|  0.651058505660742|1704563419431|
+------------------+-------------------+-------------------+-------------+


scala> spark.sql("select * from  hudi_trips_snapshot where fare > 20.0").show()
+-------------------+--------------------+--------------------+----------------------+--------------------+-------------------+-------------------+----------+-------------------+-------------------+------------------+---------+-------------+--------------------+--------------------+
|_hoodie_commit_time|_hoodie_commit_seqno|  _hoodie_record_key|_hoodie_partition_path|   _hoodie_file_name|          begin_lat|          begin_lon|    driver|            end_lat|            end_lon|              fare|    rider|           ts|                uuid|       partitionpath|
+-------------------+--------------------+--------------------+----------------------+--------------------+-------------------+-------------------+----------+-------------------+-------------------+------------------+---------+-------------+--------------------+--------------------+
|  20240109190932344|20240109190932344...|ca1d00a7-8eeb-49c...|  americas/united_s...|7608cfb3-4a20-418...| 0.1856488085068272| 0.9694586417848392|driver-213|0.38186367037201974|0.25252652214479043| 33.92216483948643|rider-213|1704256809374|ca1d00a7-8eeb-49c...|americas/united_s...|
|  20240109190932344|20240109190932344...|74e4699e-3644-477...|  americas/united_s...|7608cfb3-4a20-418...| 0.5731835407930634| 0.4923479652912024|driver-213|0.08988581780930216|0.42520899698713666| 64.27696295884016|rider-213|1704362707376|74e4699e-3644-477...|americas/united_s...|
|  20240109190932344|20240109190932344...|fb17af56-2f63-481...|  americas/united_s...|7608cfb3-4a20-418...|0.21624150367601136|0.14285051259466197|driver-213| 0.5890949624813784| 0.0966823831927115| 93.56018115236618|rider-213|1704216687193|fb17af56-2f63-481...|americas/united_s...|
|  20240109190932344|20240109190932344...|c745152f-893d-461...|  americas/united_s...|7608cfb3-4a20-418...|0.11488393157088261| 0.6273212202489661|driver-213| 0.7454678537511295| 0.3954939864908973| 27.79478688582596|rider-213|1704494741512|c745152f-893d-461...|americas/united_s...|
|  20240109190932344|20240109190932344...|d2c871b0-e98e-44e...|  americas/brazil/s...|1c69c03e-47de-4d9...| 0.6100070562136587| 0.8779402295427752|driver-213| 0.3407870505929602| 0.5030798142293655|  43.4923811219014|rider-213|1704623138251|d2c871b0-e98e-44e...|americas/brazil/s...|
|  20240109190932344|20240109190932344...|6983e2a6-61e4-4df...|  americas/brazil/s...|1c69c03e-47de-4d9...| 0.0750588760043035|0.03844104444445928|driver-213|0.04376353354538354| 0.6346040067610669| 66.62084366450246|rider-213|1704568660989|6983e2a6-61e4-4df...|americas/brazil/s...|
|  20240109190932344|20240109190932344...|58f04a7a-6d32-42a...|  americas/brazil/s...|1c69c03e-47de-4d9...| 0.4726905879569653|0.46157858450465483|driver-213|  0.754803407008858| 0.9671159942018241|34.158284716382845|rider-213|1704209002713|58f04a7a-6d32-42a...|americas/brazil/s...|
|  20240109190932344|20240109190932344...|f464f5d9-c284-4a8...|    asia/india/chennai|38325a98-dd9a-453...|  0.651058505660742| 0.8192868687714224|driver-213|0.20714896002914462|0.06224031095826987| 41.06290929046368|rider-213|1704563419431|f464f5d9-c284-4a8...|  asia/india/chennai|
+-------------------+--------------------+--------------------+----------------------+--------------------+-------------------+-------------------+----------+-------------------+-------------------+------------------+---------+-------------+--------------------+--------------------+


scala> 

029

4.2.4 更新数据

val tripsSnapshotDF1 = spark.read.format("hudi").load(basePath)
tripsSnapshotDF.createOrReplaceTempView("hudi_trips_snapshot1")

spark.sql("select _hoodie_commit_time, _hoodie_record_key, _hoodie_partition_path, rider, driver, fare from  hudi_trips_snapshot").show(20)

scala> val tripsSnapshotDF1 = spark.read.format("hudi").load(basePath)
tripsSnapshotDF1: org.apache.spark.sql.DataFrame = [_hoodie_commit_time: string, _hoodie_commit_seqno: string ... 13 more fields]

scala> tripsSnapshotDF1.createOrReplaceTempView("hudi_trips_snapshot1")

scala> spark.sql("select _hoodie_commit_time, _hoodie_record_key, _hoodie_partition_path, rider, driver, fare from  hudi_trips_snapshot").show(20)
+-------------------+--------------------+----------------------+---------+----------+------------------+
|_hoodie_commit_time|  _hoodie_record_key|_hoodie_partition_path|    rider|    driver|              fare|
+-------------------+--------------------+----------------------+---------+----------+------------------+
|  20240123152755513|c1f36d67-9031-415...|  americas/united_s...|rider-213|driver-213| 64.27696295884016|
|  20240123152755513|a1914586-f6f8-468...|  americas/united_s...|rider-213|driver-213| 33.92216483948643|
|  20240123152755513|7779f311-34fb-412...|  americas/united_s...|rider-213|driver-213| 93.56018115236618|
|  20240123152755513|bc90314b-537a-409...|  americas/united_s...|rider-213|driver-213| 27.79478688582596|
|  20240123152755513|aef5f9e3-e31a-42c...|  americas/united_s...|rider-213|driver-213|19.179139106643607|
|  20240123152755513|1dda1939-c3a7-488...|  americas/brazil/s...|rider-213|driver-213|34.158284716382845|
|  20240123152755513|7f6b775b-1480-425...|  americas/brazil/s...|rider-213|driver-213|  43.4923811219014|
|  20240123152755513|ce7f6bb2-53de-46b...|  americas/brazil/s...|rider-213|driver-213| 66.62084366450246|
|  20240123152755513|10b632a9-59e5-4ef...|    asia/india/chennai|rider-213|driver-213|17.851135255091155|
|  20240123152755513|8a78e424-e64a-40f...|    asia/india/chennai|rider-213|driver-213| 41.06290929046368|
+-------------------+--------------------+----------------------+---------+----------+------------------+


scala> 

4.2.3 查询数据

3)时间旅行查询

030

4.2.5 增量查询

scala> spark.
     |   read.
     |   format("hudi").
     |   load(basePath).
     |   createOrReplaceTempView("hudi_trips_snapshot")
                                                                                
scala> val commits = spark.sql("select distinct(_hoodie_commit_time) as commitTime from  hudi_trips_snapshot order by commitTime").map(k => k.getString(0)).take(50)
commits: Array[String] = Array(20240123152755513)                               

scala> val beginTime = commits(commits.length - 2)
java.lang.ArrayIndexOutOfBoundsException: -1
  ... 59 elided

scala> 

scala> 

scala> val updates = convertToStringList(dataGen.generateUpdates(10))
updates: java.util.List[String] = [{"ts": 1705879465411, "uuid": "c1f36d67-9031-4157-a8d2-13b6d30b1572", "rider": "rider-284", "driver": "driver-284", "begin_lat": 0.7340133901254792, "begin_lon": 0.5142184937933181, "end_lat": 0.7814655558162802, "end_lon": 0.6592596683641996, "fare": 49.527694252432056, "partitionpath": "americas/united_states/san_francisco"}, {"ts": 1705399614657, "uuid": "1dda1939-c3a7-4884-9b70-4ef87bc050f9", "rider": "rider-284", "driver": "driver-284", "begin_lat": 0.1593867607188556, "begin_lon": 0.010872312870502165, "end_lat": 0.9808530350038475, "end_lon": 0.7963756520507014, "fare": 29.47661370147079, "partitionpath": "americas/brazil/sao_paulo"}, {"ts": 1705403081035, "uuid": "1dda1939-c3a7-4884-9b70-4ef87bc050f9", "rider": "rider-...

scala> val df = spark.read.json(spark.sparkContext.parallelize(updates, 2))
warning: one deprecation (since 2.12.0)
warning: one deprecation (since 2.2.0)
warning: two deprecations in total; for details, enable `:setting -deprecation' or `:replay -deprecation'
df: org.apache.spark.sql.DataFrame = [begin_lat: double, begin_lon: double ... 8 more fields]

scala> df.write.format("hudi").
     |   options(getQuickstartWriteConfigs).
     |   option(PRECOMBINE_FIELD_OPT_KEY, "ts").
     |   option(RECORDKEY_FIELD_OPT_KEY, "uuid").
     |   option(PARTITIONPATH_FIELD_OPT_KEY, "partitionpath").
     |   option(TABLE_NAME, tableName).
     |   mode(Append).
     |   save(basePath)
warning: one deprecation; for details, enable `:setting -deprecation' or `:replay -deprecation'
                                                                                
scala> val updates = convertToStringList(dataGen.generateUpdates(10))
updates: java.util.List[String] = [{"ts": 1705790965039, "uuid": "c1f36d67-9031-4157-a8d2-13b6d30b1572", "rider": "rider-243", "driver": "driver-243", "begin_lat": 0.9045189017781902, "begin_lon": 0.38697902072535484, "end_lat": 0.21932410786717094, "end_lon": 0.7816060218244935, "fare": 44.596839246210095, "partitionpath": "americas/united_states/san_francisco"}, {"ts": 1705482677807, "uuid": "ce7f6bb2-53de-46bd-87f8-ff19f367bd1d", "rider": "rider-243", "driver": "driver-243", "begin_lat": 0.856152038750905, "begin_lon": 0.3132477949501916, "end_lat": 0.8742438057467156, "end_lon": 0.26923247017036556, "fare": 2.4995362119815567, "partitionpath": "americas/brazil/sao_paulo"}, {"ts": 1705754253073, "uuid": "c1f36d67-9031-4157-a8d2-13b6d30b1572", "rider": "rider...

scala> val df = spark.read.json(spark.sparkContext.parallelize(updates, 2))
warning: one deprecation (since 2.12.0)
warning: one deprecation (since 2.2.0)
warning: two deprecations in total; for details, enable `:setting -deprecation' or `:replay -deprecation'
df: org.apache.spark.sql.DataFrame = [begin_lat: double, begin_lon: double ... 8 more fields]

scala> df.write.format("hudi").
     |   options(getQuickstartWriteConfigs).
     |   option(PRECOMBINE_FIELD_OPT_KEY, "ts").
     |   option(RECORDKEY_FIELD_OPT_KEY, "uuid").
     |   option(PARTITIONPATH_FIELD_OPT_KEY, "partitionpath").
     |   option(TABLE_NAME, tableName).
     |   mode(Append).
     |   save(basePath)
warning: one deprecation; for details, enable `:setting -deprecation' or `:replay -deprecation'
                                                                                
scala> val updates = convertToStringList(dataGen.generateUpdates(10))
updates: java.util.List[String] = [{"ts": 1705393408046, "uuid": "10b632a9-59e5-4ef4-811c-1250a817c74a", "rider": "rider-563", "driver": "driver-563", "begin_lat": 0.16172715555352513, "begin_lon": 0.6286940931025506, "end_lat": 0.7559063825441225, "end_lon": 0.39828516291900906, "fare": 16.098476392187365, "partitionpath": "asia/india/chennai"}, {"ts": 1705982569737, "uuid": "8a78e424-e64a-40f8-8eb7-f8e3741ab17e", "rider": "rider-563", "driver": "driver-563", "begin_lat": 0.9312237784651692, "begin_lon": 0.67243450582925, "end_lat": 0.28393433672984614, "end_lon": 0.2725166210142148, "fare": 27.603571822228822, "partitionpath": "asia/india/chennai"}, {"ts": 1705602950761, "uuid": "bc90314b-537a-409e-9d93-9c8663d578cc", "rider": "rider-563", "driver": "driver-5...

scala> val df = spark.read.json(spark.sparkContext.parallelize(updates, 2))
warning: one deprecation (since 2.12.0)
warning: one deprecation (since 2.2.0)
warning: two deprecations in total; for details, enable `:setting -deprecation' or `:replay -deprecation'
df: org.apache.spark.sql.DataFrame = [begin_lat: double, begin_lon: double ... 8 more fields]

scala> df.write.format("hudi").
     |   options(getQuickstartWriteConfigs).
     |   option(PRECOMBINE_FIELD_OPT_KEY, "ts").
     |   option(RECORDKEY_FIELD_OPT_KEY, "uuid").
     |   option(PARTITIONPATH_FIELD_OPT_KEY, "partitionpath").
     |   option(TABLE_NAME, tableName).
     |   mode(Append).
     |   save(basePath)
warning: one deprecation; for details, enable `:setting -deprecation' or `:replay -deprecation'

scala> 

scala> 

scala> spark.
     |   read.
     |   format("hudi").
     |   load(basePath).
     |   createOrReplaceTempView("hudi_trips_snapshot")
                                                                                
scala> val commits = spark.sql("select distinct(_hoodie_commit_time) as commitTime from  hudi_trips_snapshot order by commitTime").map(k => k.getString(0)).take(50)
commits: Array[String] = Array(20240123155641315, 20240123155717896, 20240123155726796)

scala> val beginTime = commits(commits.length - 2)
beginTime: String = 20240123155717896

scala> val tripsIncrementalDF = spark.read.format("hudi").
     |   option(QUERY_TYPE_OPT_KEY, QUERY_TYPE_INCREMENTAL_OPT_VAL).
     |   option(BEGIN_INSTANTTIME_OPT_KEY, beginTime).
     |   load(basePath)
tripsIncrementalDF: org.apache.spark.sql.DataFrame = [_hoodie_commit_time: string, _hoodie_commit_seqno: string ... 13 more fields]

scala> tripsIncrementalDF.createOrReplaceTempView("hudi_trips_incremental")

scala> spark.sql("select `_hoodie_commit_time`, fare, begin_lon, begin_lat, ts from  hudi_trips_incremental where fare > 20.0").show()
+-------------------+------------------+-------------------+------------------+-------------+
|_hoodie_commit_time|              fare|          begin_lon|         begin_lat|           ts|
+-------------------+------------------+-------------------+------------------+-------------+
|  20240123155726796| 54.16944371261484| 0.7548086309564753|0.5535762898838785|1705960250638|
|  20240123155726796| 37.35848234860164| 0.9084944020139248|0.6330100459693088|1705652568556|
|  20240123155726796| 84.66949742559657|0.31331111382522836|0.8573834026158349|1705867633650|
|  20240123155726796|  38.4828225162323|0.20404106962358204|0.1450793330198833|1705405789140|
|  20240123155726796| 55.31092276192561|  0.826183030502974| 0.391583018565109|1705428608507|
|  20240123155726796|27.603571822228822|   0.67243450582925|0.9312237784651692|1705982569737|
+-------------------+------------------+-------------------+------------------+-------------+


scala> 

4.2.6 指定时间点查询

scala> val beginTime = "000" 
beginTime: String = 000

scala> val endTime = commits(commits.length - 2) 
endTime: String = 20240123155717896

scala> val tripsPointInTimeDF = spark.read.format("hudi").
     |   option(QUERY_TYPE_OPT_KEY, QUERY_TYPE_INCREMENTAL_OPT_VAL).
     |   option(BEGIN_INSTANTTIME_OPT_KEY, beginTime).
     |   option(END_INSTANTTIME_OPT_KEY, endTime).
     |   load(basePath)
tripsPointInTimeDF: org.apache.spark.sql.DataFrame = [_hoodie_commit_time: string, _hoodie_commit_seqno: string ... 13 more fields]

scala> tripsPointInTimeDF.createOrReplaceTempView("hudi_trips_point_in_time")

scala> spark.sql("select `_hoodie_commit_time`, fare, begin_lon, begin_lat, ts from hudi_trips_point_in_time where fare > 20.0").show()
+-------------------+------------------+-------------------+-------------------+-------------+
|_hoodie_commit_time|              fare|          begin_lon|          begin_lat|           ts|
+-------------------+------------------+-------------------+-------------------+-------------+
|  20240123155717896|44.596839246210095|0.38697902072535484| 0.9045189017781902|1705790965039|
|  20240123155641315|  90.9053809533154|0.19949323322922063|0.18294079059016366|1705742911148|
|  20240123155717896|26.636532270940915|0.12314538318119372|0.35527775182006427|1705655264707|
|  20240123155717896| 51.42305232303094| 0.7071871604905721|  0.876334576190389|1705609025064|
|  20240123155641315| 91.99515909032544| 0.2783086084578943| 0.2110206104048945|1705585303503|
|  20240123155717896| 89.45841313717807|0.22991770617403628| 0.6923616674358241|1705771716835|
|  20240123155717896| 71.08018349571618| 0.8150991077375751|0.01925237918893319|1705812754018|
+-------------------+------------------+-------------------+-------------------+-------------+


scala> 

031

4.2.7 删除数据

3.2.6 删除策略

1)逻辑删:将 value 字段全部标记为 null。

2)物理删:

(1)通过 OPERATION_OPT_KEY  删除所有的输入记录

(2)配置 PAYLOAD_CLASS_OPT_KEY = org.apache.hudi.EmptyHoodieRecordPayload 删除所有的输入记录

(3)在输入记录添加字段:_hoodie_is_deleted

4.2.8 覆盖数据

032

4.3 Spark SQL方式

4.3.1 创建表

[atguigu@node001 ~]$ nohup hive --service metastore &
[1] 11371
[atguigu@node001 ~]$ nohup: 忽略输入并把输出追加到"nohup.out"

[atguigu@node001 ~]$ jpsall
================ node001 ================
3472 NameNode
4246 NodeManager
4455 JobHistoryServer
11384 -- process information unavailable
10456 SparkSubmit
3642 DataNode
4557 SparkSubmit
11437 Jps
================ node002 ================
6050 Jps
2093 DataNode
2495 NodeManager
2335 ResourceManager
================ node003 ================
5685 Jps
2279 SecondaryNameNode
2459 NodeManager
2159 DataNode
[atguigu@node001 ~]$ netstat -anp | grep 9083
(Not all processes could be identified, non-owned process info
 will not be shown, you would have to be root to see it all.)
tcp6       0      0 :::9083                 :::*                    LISTEN      11371/java          
[atguigu@node001 ~]$ spark-sql \
>   --conf 'spark.serializer=org.apache.spark.serializer.KryoSerializer' \
>   --conf 'spark.sql.catalog.spark_catalog=org.apache.spark.sql.hudi.catalog.HoodieCatalog' \
>   --conf 'spark.sql.extensions=org.apache.spark.sql.hudi.HoodieSparkSessionExtension'
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
0    [main] WARN  org.apache.hadoop.util.NativeCodeLoader  - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
1410 [main] WARN  org.apache.hadoop.hive.conf.HiveConf  - HiveConf of name hive.metastore.event.db.notification.api.auth does not exist
1410 [main] WARN  org.apache.hadoop.hive.conf.HiveConf  - HiveConf of name hive.server2.active.passive.ha.enable does not exist
8317 [main] WARN  org.apache.spark.util.Utils  - Service 'SparkUI' could not bind on port 4040. Attempting port 4041.
8319 [main] WARN  org.apache.spark.util.Utils  - Service 'SparkUI' could not bind on port 4041. Attempting port 4042.
Spark master: local[*], Application Id: local-1706012797408
spark-sql (default)> show databases;
namespace
default
edu2077
Time taken: 11.185 seconds, Fetched 2 row(s)
spark-sql (default)> 
                   > create database spark_hudi;
Response code
Time taken: 11.725 seconds
spark-sql (default)> use spark_hudi;
Response code
Time taken: 0.673 seconds
spark-sql (default)> create table hudi_cow_nonpcf_tbl (
                   >   uuid int,
                   >   name string,
                   >   price double
                   > ) using hudi;
422168 [main] WARN  org.apache.hudi.common.config.DFSPropertiesConfiguration  - Cannot find HUDI_CONF_DIR, please set it as the dir of hudi-defaults.conf
422406 [main] WARN  org.apache.hudi.common.config.DFSPropertiesConfiguration  - Properties file file:/etc/hudi/conf/hudi-defaults.conf not found. Ignoring to load props file
425565 [main] WARN  org.apache.hadoop.hive.ql.session.SessionState  - METASTORE_FILTER_HOOK will be ignored, since hive.security.authorization.manager is set to instance of HiveAuthorizerFactory.
Response code
Time taken: 10.492 seconds
spark-sql (default)> show tables;
namespace       tableName       isTemporary
hudi_cow_nonpcf_tbl
Time taken: 1.444 seconds, Fetched 1 row(s)
spark-sql (default)> desc hudi_cow_nonpcf_tbl;
col_name        data_type       comment
_hoodie_commit_time     string                                      
_hoodie_commit_seqno    string                                      
_hoodie_record_key      string                                      
_hoodie_partition_path  string                                      
_hoodie_file_name       string                                      
uuid                    int                                         
name                    string                                      
price                   double                                      
Time taken: 2.179 seconds, Fetched 8 row(s)
spark-sql (default)> create table hudi_mor_tbl (
                   >   id int,
                   >   name string,
                   >   price double,
                   >   ts bigint
                   > ) using hudi
                   > tblproperties (
                   >   type = 'mor',
                   >   primaryKey = 'id',
                   >   preCombineField = 'ts'
                   > );
Response code
Time taken: 1.803 seconds
spark-sql (default)> show tables;
namespace       tableName       isTemporary
hudi_cow_nonpcf_tbl
hudi_mor_tbl
Time taken: 0.257 seconds, Fetched 2 row(s)
spark-sql (default)> desc hudi_mor_tbl;
col_name        data_type       comment
_hoodie_commit_time     string                                      
_hoodie_commit_seqno    string                                      
_hoodie_record_key      string                                      
_hoodie_partition_path  string                                      
_hoodie_file_name       string                                      
id                      int                                         
name                    string                                      
price                   double                                      
ts                      bigint                                      
Time taken: 0.636 seconds, Fetched 9 row(s)
spark-sql (default)> create table hudi_cow_pt_tbl (
                   >   id bigint,
                   >   name string,
                   >   ts bigint,
                   >   dt string,
                   >   hh string
                   > ) using hudi
                   > tblproperties (
                   >   type = 'cow',
                   >   primaryKey = 'id',
                   >   preCombineField = 'ts'
                   >  )
                   > partitioned by (dt, hh)
                   > location '/tmp/hudi/hudi_cow_pt_tbl';
Response code
Time taken: 21.88 seconds
spark-sql (default)> create table hudi_ctas_cow_nonpcf_tbl
                   > using hudi
                   > tblproperties (primaryKey = 'id')
                   > as
                   > select 1 as id, 'a1' as name, 10 as price;
1514254 [main] WARN  org.apache.hudi.metadata.HoodieBackedTableMetadata  - Metadata table was not found at path file:/home/atguigu/spark-warehouse/spark_hudi.db/hudi_ctas_cow_nonpcf_tbl/.hoodie/metadata
1546852 [main] WARN  org.apache.hadoop.hive.conf.HiveConf  - HiveConf of name hive.metastore.event.db.notification.api.auth does not exist
1546852 [main] WARN  org.apache.hadoop.hive.conf.HiveConf  - HiveConf of name hive.server2.active.passive.ha.enable does not exist
Response code
Time taken: 63.078 seconds
spark-sql (default)> select * from hudi_ctas_cow_nonpcf_tbl;
_hoodie_commit_time     _hoodie_commit_seqno    _hoodie_record_key      _hoodie_partition_path  _hoodie_file_name       id      name    price
20240123205131373       20240123205131373_0_0   id:1            bee32427-f490-40dd-89ed-3bacd3adf6fb-0_0-17-15_20240123205131373.parquet        1       a1   10
Time taken: 1.636 seconds, Fetched 1 row(s)
spark-sql (default)> create table hudi_ctas_cow_pt_tbl
                   > using hudi
                   > tblproperties (type = 'cow', primaryKey = 'id', preCombineField = 'ts')
                   > partitioned by (dt)
                   > as
                   > select 1 as id, 'a1' as name, 10 as price, 1000 as ts, '2021-12-01' as dt;
1646675 [main] WARN  org.apache.hudi.metadata.HoodieBackedTableMetadata  - Metadata table was not found at path file:/home/atguigu/spark-warehouse/spark_hudi.db/hudi_ctas_cow_pt_tbl/.hoodie/metadata
1664435 [main] WARN  org.apache.hadoop.hive.conf.HiveConf  - HiveConf of name hive.metastore.event.db.notification.api.auth does not exist
1664435 [main] WARN  org.apache.hadoop.hive.conf.HiveConf  - HiveConf of name hive.server2.active.passive.ha.enable does not exist
Response code
Time taken: 26.019 seconds
spark-sql (default)> select * from hudi_ctas_cow_pt_tbl;
_hoodie_commit_time     _hoodie_commit_seqno    _hoodie_record_key      _hoodie_partition_path  _hoodie_file_name       id      name    price   ts      dt
20240123205354771       20240123205354771_0_0   id:1    dt=2021-12-01   88ad8031-2239-4bce-8494-5bf109012400-0_0-69-1259_20240123205354771.parquet      1    a1       10      1000    2021-12-01
Time taken: 2.829 seconds, Fetched 1 row(s)
spark-sql (default)> 

033

4.3.2 插入数据

spark-sql (default)> show tables;
namespace       tableName       isTemporary
hudi_cow_nonpcf_tbl
hudi_cow_pt_tbl
hudi_ctas_cow_nonpcf_tbl
hudi_ctas_cow_pt_tbl
hudi_mor_tbl
Time taken: 1.298 seconds, Fetched 5 row(s)
spark-sql (default)> insert into hudi_cow_nonpcf_tbl 1, 'a1', 20;
Error in query: 
mismatched input '1' expecting {'(', 'FROM', 'MAP', 'REDUCE', 'SELECT', 'TABLE', 'VALUES'}(line 1, pos 32)

== SQL ==
insert into hudi_cow_nonpcf_tbl 1, 'a1', 20
--------------------------------^^^

spark-sql (default)> insert into hudi_cow_nonpcf_tbl select 1, 'a1', 20;
458055 [main] WARN  org.apache.hudi.common.config.DFSPropertiesConfiguration  - Cannot find HUDI_CONF_DIR, please set it as the dir of hudi-defaults.conf
458212 [main] WARN  org.apache.hudi.common.config.DFSPropertiesConfiguration  - Properties file file:/etc/hudi/conf/hudi-defaults.conf not found. Ignoring to load props file
475300 [main] WARN  org.apache.hudi.metadata.HoodieBackedTableMetadata  - Metadata table was not found at path file:/home/atguigu/spark-warehouse/spark_hudi.db/hudi_cow_nonpcf_tbl/.hoodie/metadata
517206 [main] WARN  org.apache.hadoop.hive.conf.HiveConf  - HiveConf of name hive.metastore.event.db.notification.api.auth does not exist
517206 [main] WARN  org.apache.hadoop.hive.conf.HiveConf  - HiveConf of name hive.server2.active.passive.ha.enable does not exist
Response code
Time taken: 80.477 seconds
spark-sql (default)> insert into hudi_mor_tbl select 1, 'a1', 20, 1000;
640716 [main] WARN  org.apache.hudi.metadata.HoodieBackedTableMetadata  - Metadata table was not found at path file:/home/atguigu/spark-warehouse/spark_hudi.db/hudi_mor_tbl/.hoodie/metadata
694713 [main] WARN  org.apache.hadoop.hive.conf.HiveConf  - HiveConf of name hive.metastore.event.db.notification.api.auth does not exist
694723 [main] WARN  org.apache.hadoop.hive.conf.HiveConf  - HiveConf of name hive.server2.active.passive.ha.enable does not exist
Response code
Time taken: 71.597 seconds
spark-sql (default)> insert into hudi_cow_pt_tbl partition (dt, hh)
                   > select 1 as id, 'a1' as name, 1000 as ts, '2021-12-09' as dt, '10' as hh;
743011 [main] WARN  org.apache.hudi.metadata.HoodieBackedTableMetadata  - Metadata table was not found at path hdfs://node001:8020/tmp/hudi/hudi_cow_pt_tbl/.hoodie/metadata
04:48  WARN: Timeline-server-based markers are not supported for HDFS: base path hdfs://node001:8020/tmp/hudi/hudi_cow_pt_tbl.  Falling back to direct markers.
04:49  WARN: Timeline-server-based markers are not supported for HDFS: base path hdfs://node001:8020/tmp/hudi/hudi_cow_pt_tbl.  Falling back to direct markers.
04:53  WARN: Timeline-server-based markers are not supported for HDFS: base path hdfs://node001:8020/tmp/hudi/hudi_cow_pt_tbl.  Falling back to direct markers.
Response code
Time taken: 46.44 seconds
spark-sql (default)> insert into hudi_cow_pt_tbl partition(dt = '2021-12-09', hh='11') select 2, 'a2', 1000;
10:06  WARN: Timeline-server-based markers are not supported for HDFS: base path hdfs://node001:8020/tmp/hudi/hudi_cow_pt_tbl.  Falling back to direct markers.
10:07  WARN: Timeline-server-based markers are not supported for HDFS: base path hdfs://node001:8020/tmp/hudi/hudi_cow_pt_tbl.  Falling back to direct markers.
10:11  WARN: Timeline-server-based markers are not supported for HDFS: base path hdfs://node001:8020/tmp/hudi/hudi_cow_pt_tbl.  Falling back to direct markers.
Response code
Time taken: 71.592 seconds
spark-sql (default)> select * from hudi_mor_tbl;
_hoodie_commit_time     _hoodie_commit_seqno    _hoodie_record_key      _hoodie_partition_path  _hoodie_file_name       id      name    price   ts
20240125160415749       20240125160415749_0_0   id:1            a81ca1da-f642-45c5-ac7e-eb93de803ba8-0_0-65-1253_20240125160415749.parquet      1       a1     20.0     1000
Time taken: 23.135 seconds, Fetched 1 row(s)
spark-sql (default)> -- 向指定preCombineKey的表插入数据,则写操作为upsert
spark-sql (default)> insert into hudi_mor_tbl select 1, 'a1_1', 20, 1001;
1353572 [main] WARN  org.apache.hadoop.hive.conf.HiveConf  - HiveConf of name hive.metastore.event.db.notification.api.auth does not exist
1353573 [main] WARN  org.apache.hadoop.hive.conf.HiveConf  - HiveConf of name hive.server2.active.passive.ha.enable does not exist
Response code
Time taken: 46.455 seconds
spark-sql (default)> select id, name, price, ts from hudi_mor_tbl;
id      name    price   ts
1       a1_1    20.0    1001
Time taken: 2.081 seconds, Fetched 1 row(s)
spark-sql (default)> set hoodie.sql.bulk.insert.enable=true;
key     value
hoodie.sql.bulk.insert.enable   true
Time taken: 0.214 seconds, Fetched 1 row(s)
spark-sql (default)> set hoodie.sql.insert.mode=non-strict;
key     value
hoodie.sql.insert.mode  non-strict
Time taken: 0.027 seconds, Fetched 1 row(s)
spark-sql (default)> insert into hudi_mor_tbl select 1, 'a1_2', 20, 1002;
1538483 [main] WARN  org.apache.hadoop.hive.conf.HiveConf  - HiveConf of name hive.metastore.event.db.notification.api.auth does not exist
1538486 [main] WARN  org.apache.hadoop.hive.conf.HiveConf  - HiveConf of name hive.server2.active.passive.ha.enable does not exist
Response code
Time taken: 42.906 seconds
spark-sql (default)> select id, name, price, ts from hudi_mor_tbl;
id      name    price   ts
1       a1_2    20.0    1002
1       a1_1    20.0    1001
Time taken: 1.015 seconds, Fetched 2 row(s)
spark-sql (default)> set hoodie.sql.bulk.insert.enable=false;
key     value
hoodie.sql.bulk.insert.enable   false
Time taken: 2.396 seconds, Fetched 1 row(s)
spark-sql (default)> create table hudi_cow_pt_tbl1 (
                   >   id bigint,
                   >   name string,
                   >   ts bigint,
                   >   dt string,
                   >   hh string
                   > ) using hudi
                   > tblproperties (
                   >   type = 'cow',
                   >   primaryKey = 'id',
                   >   preCombineField = 'ts'
                   >  )
                   > partitioned by (dt, hh)
                   > location '/tmp/hudi/hudi_cow_pt_tbl1';
1737608 [main] WARN  org.apache.hadoop.hive.ql.session.SessionState  - METASTORE_FILTER_HOOK will be ignored, since hive.security.authorization.manager is set to instance of HiveAuthorizerFactory.
Response code
Time taken: 12.013 seconds
spark-sql (default)> insert into hudi_cow_pt_tbl1 select 1, 'a0', 1000, '2021-12-09', '10';
1765548 [main] WARN  org.apache.hudi.metadata.HoodieBackedTableMetadata  - Metadata table was not found at path hdfs://node001:8020/tmp/hudi/hudi_cow_pt_tbl1/.hoodie/metadata
22:14  WARN: Timeline-server-based markers are not supported for HDFS: base path hdfs://node001:8020/tmp/hudi/hudi_cow_pt_tbl1.  Falling back to direct markers.
22:15  WARN: Timeline-server-based markers are not supported for HDFS: base path hdfs://node001:8020/tmp/hudi/hudi_cow_pt_tbl1.  Falling back to direct markers.
22:23  WARN: Timeline-server-based markers are not supported for HDFS: base path hdfs://node001:8020/tmp/hudi/hudi_cow_pt_tbl1.  Falling back to direct markers.
Response code
Time taken: 64.552 seconds
spark-sql (default)> select * from hudi_cow_pt_tbl1;
_hoodie_commit_time     _hoodie_commit_seqno    _hoodie_record_key      _hoodie_partition_path  _hoodie_file_name       id      name    ts      dt      hh
20240125162301446       20240125162301446_0_0   id:1    dt=2021-12-09/hh=10     1e1b2016-8b33-4d4b-a824-4cd53ab7e8ec-0_0-290-5658_20240125162301446.parquet    1a0      1000    2021-12-09      10
Time taken: 1.702 seconds, Fetched 1 row(s)
spark-sql (default)> insert into hudi_cow_pt_tbl1 select 1, 'a1', 1001, '2021-12-09', '10';
23:04  WARN: Timeline-server-based markers are not supported for HDFS: base path hdfs://node001:8020/tmp/hudi/hudi_cow_pt_tbl1.  Falling back to direct markers.
23:05  WARN: Timeline-server-based markers are not supported for HDFS: base path hdfs://node001:8020/tmp/hudi/hudi_cow_pt_tbl1.  Falling back to direct markers.
23:09  WARN: Timeline-server-based markers are not supported for HDFS: base path hdfs://node001:8020/tmp/hudi/hudi_cow_pt_tbl1.  Falling back to direct markers.
Response code
Time taken: 16.112 seconds
spark-sql (default)> select * from hudi_cow_pt_tbl1;
_hoodie_commit_time     _hoodie_commit_seqno    _hoodie_record_key      _hoodie_partition_path  _hoodie_file_name       id      name    ts      dt      hh
20240125162431677       20240125162431677_0_0   id:1    dt=2021-12-09/hh=10     1e1b2016-8b33-4d4b-a824-4cd53ab7e8ec-0_0-329-6292_20240125162431677.parquet    1a1      1001    2021-12-09      10
Time taken: 1.122 seconds, Fetched 1 row(s)
spark-sql (default)> select * from hudi_cow_pt_tbl1 timestamp as of '20220307091628793' where id = 1;
_hoodie_commit_time     _hoodie_commit_seqno    _hoodie_record_key      _hoodie_partition_path  _hoodie_file_name       id      name    ts      dt      hh
Time taken: 20.962 seconds
spark-sql (default)> 

034

4.3.4 更新数据

1)update

035

4.3.4 更新数据

2)MergeInto

本文来自互联网用户投稿,该文观点仅代表作者本人,不代表本站立场。本站仅提供信息存储空间服务,不拥有所有权,不承担相关法律责任。如若转载,请注明出处:http://www.coloradmin.cn/o/1928584.html

如若内容造成侵权/违法违规/事实不符,请联系多彩编程网进行投诉反馈,一经查实,立即删除!

相关文章

【ARM】MDK-服务器与客户端不同网段内出现卡顿问题

【更多软件使用问题请点击亿道电子官方网站】 1、 文档目标 记录不同网段之间的请求发送情况以及MDK网络版license文件内设置的影响。 2、 问题场景 客户使用很久的MDK网络版,在获取授权时都会出现4-7秒的卡顿,无法对keil进行任何操作,彻底…

Mac 如何安装vscode

Mac 电脑/ 苹果电脑如何安装 vscode 下载安装包 百度搜索vscode,即可得到vscode的官方下载地址:https://code.visualstudio.com/ 访问网页,点击下载即可。 下载完成后,得到下图所示的app。 将该 app 文件,放入到…

CV11_模型部署pytorch转ONNX

如果自己的模型中的一些算子,ONNX内部没有,那么需要自己去实现。 1.1 配置环境 安装ONNX pip install onnx -i https://pypi.tuna.tsinghua.edu.cn/simple 安装推理引擎ONNX Runtime pip install onnxruntime -i https://pypi.tuna.tsinghua.edu.cn/si…

基于STM32设计的超声波测距仪(微信小程序)(186)

基于STM32设计的超声波测距仪(微信小程序)(186) 文章目录 一、前言1.1 项目介绍【1】项目功能介绍【2】项目硬件模块组成1.2 设计思路【1】整体设计思路【2】ESP8266工作模式配置1.3 项目开发背景【1】选题的意义【2】可行性分析【3】参考文献1.4 开发工具的选择1.5 系统框架图…

WebSocket、服务器推送技术

WebSocket 是一种在单个 TCP 连接上进行 全双工 通信的协议,它可以让客户端和服务器之间进行实时的双向通信,且不存在同源策略限制 WebSocket 使用一个长连接,在客户端和服务器之间保持持久的连接,从而可以实时地发送和接收数据…

实现给Nginx的指定网站开启basic认证——http基本认证

一、问题描述 目前我们配置的网站内容都是没有限制,可以让任何人打开浏览器都能够访问,这样就会存在一个问题(可能会存在一些恶意访问的用户进行恶意操作,直接访问到我们的敏感后台路径进行操作,风险就会很大&#xff…

如何在excel表中实现单元格满足条件时整行变色?

可以试试使用条件格式: 一、条件格式 所谓“自动变色”就要使用条件格式。 先简单模拟数据如下, 按 B列数字为偶数 为条件,整行标记为蓝色背景色。 可以这样设置: 先选中1:10行数据,在这里要确定一下名称栏里显示…

数据的力量:Facebook如何通过数据分析驱动创新

在当今数字化和信息化的时代,数据被认为是推动企业创新和发展的关键因素之一。作为全球最大的社交媒体平台,Facebook不仅积累了庞大的用户数据,还利用先进的数据分析技术,不断探索和实现新的创新。本文将深入探讨Facebook如何通过…

Golang中读写锁的底层实现

目录 Sync.RWMutex 背景与机制 接口简单介绍 sync.RWMutex 数据结构 读锁流程 RLock RUnlock RWMutex.rUnlockSlow 写锁流程 Lock Unlock Sync.RWMutex 背景与机制 从逻辑上,可以把 RWMutex 理解为一把读锁加一把写锁; 写锁具有严格的排他性&…

Spring之事务管理TranscationManager(大合集)

原子性 事务是数据库的逻辑工作单位,事务中包括的诸操作要么全做,要么全不做。 一致性 事务执行的结果必须是使数据库从一个一致性状态变到另一个一致性状态。一致性与原子性是密切相关的。 隔离性 一个事务的执行不能被其他事务干扰。 持续性 一…

人工智能算法工程师(中级)课程12-PyTorch神经网络之LSTM和GRU网络与代码详解1

大家好,我是微学AI,今天给大家介绍一下人工智能算法工程师(中级)课程12-PyTorch神经网络之LSTM和GRU网络与代码详解。在深度学习领域,循环神经网络(RNN)因其处理序列数据的能力而备受关注。然而,传统的RNN存在梯度消失和梯度爆炸的问题,这使得它在长序列任务中的表现不尽…

【Git分支管理】理解分支 | 创建分支 | 切换分支 | 合并分支 | 删除分支 | 强制删除分支

目录 前言 0.理解分支 1.查看本地仓库存在的分支 2.HEAD指向分支 3.创建本地分支 4.切换分支 5.分支提交操作 6.合并分支 快进模式Fast-forward 7.删除分支 8.强制删除分支 本篇开始介绍下Git提供的杀手级的功能:分支管理 先提交再合并 前言 在玄幻武侠…

IP-Guard日志数据上传至 SYSLOG 服务器操作指南

一、功能简介 服务器支持把日志数据上传到 SYSLOG 服务器。 二、功能配置 2.1 数据目录移交设置 在服务器安装目录下 OServer3.ini 文件中,添加工具启动配置,配置五分钟内生效。 Path:设置移交目录路径,IPG 服务器会把收集完成的…

Redis④ —— 高可用

1. 主从复制 一主多从模式,采用读写分离的方式主服务器可以进行读写操作,当发生写操作时自动将写操作同步给从服务器,而从服务器一般是只读,并接受主服务器同步过来写操作命令,然后执行这条命令。主从服务器之间的命令…

jvm常用密令、jvm性能优化、jvm性能检测、Java jstat密令使用、Java自带工具、Java jmap使用

1.jps是Java虚拟机的进程状态工具,用于列出正在运行的Java进程 jps命令的使用:cmd打开直接jps 1.1不带参数: jps 默认情况下,列出所有正在运行的 Java 进程的进程 ID 和主类名。 1.2 -l:显示完整的主类名或 JAR 文件…

《故障复盘 · 数据库连接异常关闭》

📢 大家好,我是 【战神刘玉栋】,有10多年的研发经验,致力于前后端技术栈的知识沉淀和传播。 💗 🌻 CSDN入驻不久,希望大家多多支持,后续会继续提升文章质量,绝不滥竽充数…

不开放80或443端口也能申请IP SSL证书!

在申请SSL/HTTPS证书时,如果不方便使用域名或者没有域名,就要申请一种特殊的SSL证书——IP SSL证书。但是一般的IP地址证书签发过程中,需要短暂开放80或者443端口才能签发成功。那么问题来了,有的实在不能开放80或者443端口&#…

keil中GD32 MCU IAP中APP的存储地址如何设置?

前面和大家聊过什么是IAP,那么IAP中APP的存储地址该如何设置呢? 以keil为例,打开工程的option选项卡: 将IROM1中的地址改为你想要保存的位置,比如0x08008000开始的位置: 这样通过keil烧录,程序…

记录|.NET上位机开发和PLC通信的实现

本文记录源自:B站视频 实验结果:跟视频做下来是没有问题的。能运行。 目录 前言一、项目Step1. 创建项目Step2. 创建动态图片展示Step3. 创建图片型按钮Step4. 创建下拉框Step1~4的效果展示Step5. 编程实体类操作类Main函数 Step1~5的效果展示Main函数 最…

[Python学习篇] Python PyMysql

什么是PyMysql PyMysql是一个纯 Python 实现的 MySQL 客户端库,允许你在 Python 程序中与 MySQL 数据库进行交互。 安装PyMysql PyMysql地址:https://pypi.org/project/PyMySQL/ pip install pymysql 使用PyMysql 连接mysql import pymysql# 数据库连…