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maxwell | Maxwell 's daemon , a mysql-to-json kafka producer | Pub Sub library

 by   zendesk Java Version: v1.37.5 License: Non-SPDX

 by   zendesk Java Version: v1.37.5 License: Non-SPDX

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kandi X-RAY | maxwell Summary

maxwell is a Java library typically used in Messaging, Pub Sub, Kafka applications. maxwell has no bugs, it has no vulnerabilities, it has build file available and it has high support. However maxwell has a Non-SPDX License. You can download it from GitHub, Maven.
This is Maxwell's daemon, an application that reads MySQL binlogs and writes row updates as JSON to Kafka, Kinesis, or other streaming platforms. Maxwell has low operational overhead, requiring nothing but mysql and a place to write to. Its common use cases include ETL, cache building/expiring, metrics collection, search indexing and inter-service communication. Maxwell gives you some of the benefits of event sourcing without having to re-architect your entire platform.
Support
Support
Quality
Quality
Security
Security
License
License
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kandi-support Support

  • maxwell has a highly active ecosystem.
  • It has 3224 star(s) with 869 fork(s). There are 526 watchers for this library.
  • There were 10 major release(s) in the last 12 months.
  • There are 154 open issues and 790 have been closed. On average issues are closed in 49 days. There are 42 open pull requests and 0 closed requests.
  • It has a negative sentiment in the developer community.
  • The latest version of maxwell is v1.37.5
maxwell Support
Best in #Pub Sub
Average in #Pub Sub
maxwell Support
Best in #Pub Sub
Average in #Pub Sub

quality kandi Quality

  • maxwell has 0 bugs and 0 code smells.
maxwell Quality
Best in #Pub Sub
Average in #Pub Sub
maxwell Quality
Best in #Pub Sub
Average in #Pub Sub

securitySecurity

  • maxwell has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • maxwell code analysis shows 0 unresolved vulnerabilities.
  • There are 0 security hotspots that need review.
maxwell Security
Best in #Pub Sub
Average in #Pub Sub
maxwell Security
Best in #Pub Sub
Average in #Pub Sub

license License

  • maxwell has a Non-SPDX License.
  • Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.
maxwell License
Best in #Pub Sub
Average in #Pub Sub
maxwell License
Best in #Pub Sub
Average in #Pub Sub

buildReuse

  • maxwell releases are available to install and integrate.
  • Deployable package is available in Maven.
  • Build file is available. You can build the component from source.
  • Installation instructions are not available. Examples and code snippets are available.
  • maxwell saves you 9510 person hours of effort in developing the same functionality from scratch.
  • It has 21231 lines of code, 1781 functions and 244 files.
  • It has medium code complexity. Code complexity directly impacts maintainability of the code.
maxwell Reuse
Best in #Pub Sub
Average in #Pub Sub
maxwell Reuse
Best in #Pub Sub
Average in #Pub Sub
Top functions reviewed by kandi - BETA

kandi has reviewed maxwell and discovered the below as its top functions. This is intended to give you an instant insight into maxwell implemented functionality, and help decide if they suit your requirements.

  • Validate the options .
    • Updates the maxwells schema .
      • Serialize this record to JSON .
        • MurmurHash3 32 .
          • Restore full schema .
            • Set up the metrics .
              • Extracts the row indices from the begin event .
                • Deserialize from JSON .
                  • Called to reset the column definition
                    • Determine the differences between two columns

                      Get all kandi verified functions for this library.

                      Get all kandi verified functions for this library.

                      maxwell Key Features

                      Maxwell's daemon, a mysql-to-json kafka producer

                      default

                      copy iconCopydownload iconDownload
                        mysql> insert into `test`.`maxwell` set id = 1, daemon = 'Stanislaw Lem';
                        maxwell: {
                          "database": "test",
                          "table": "maxwell",
                          "type": "insert",
                          "ts": 1449786310,
                          "xid": 940752,
                          "commit": true,
                          "data": { "id":1, "daemon": "Stanislaw Lem" }
                        }
                      

                      Could not find any factory for identifier 'avro-confluent' that implements 'org.apache.flink.table.factories.DeserializationFormatFactory'

                      copy iconCopydownload iconDownload
                      lazy val mergeStrategy = Seq(
                        assembly / assemblyMergeStrategy := {
                          case "application.conf" => MergeStrategy.concat
                          case "reference.conf" => MergeStrategy.concat
                          case m if m.toLowerCase.endsWith("manifest.mf") => MergeStrategy.discard
                          case m if m.toLowerCase.matches("meta-inf.*\\.sf$") => MergeStrategy.discard
                          case _ => MergeStrategy.first
                        }
                      )
                      
                      case "META-INF/services/org.apache.flink.table.factories.Factory"  => MergeStrategy.concat
                      case "META-INF/services/org.apache.flink.table.factories.TableFactory"  => MergeStrategy.concat
                      
                      lazy val mergeStrategy = Seq(
                        assembly / assemblyMergeStrategy := {
                          case "application.conf" => MergeStrategy.concat
                          case "reference.conf" => MergeStrategy.concat
                          case m if m.toLowerCase.endsWith("manifest.mf") => MergeStrategy.discard
                          case m if m.toLowerCase.matches("meta-inf.*\\.sf$") => MergeStrategy.discard
                          case _ => MergeStrategy.first
                        }
                      )
                      
                      case "META-INF/services/org.apache.flink.table.factories.Factory"  => MergeStrategy.concat
                      case "META-INF/services/org.apache.flink.table.factories.TableFactory"  => MergeStrategy.concat
                      

                      get porper listbox item when using trace

                      copy iconCopydownload iconDownload
                      def sauthor_list(self):
                          caut = frame1_lb.curselection()
                          print(caut)
                          saut = frame1_lb.get(caut[0])  # get the selected item
                          print(saut)
                      

                      Insert colA into DF1 with vals from DF2['colB'] by matching colC in both DFs

                      copy iconCopydownload iconDownload
                      import pandas as pd
                      dfa = pd.read_csv('csv_a.csv')
                      dfa.set_index('StockID', inplace=True)
                      dfb = pd.read_csv('csv_b.csv')
                      
                      #remove incomplete rows (i.e. without Category/StockID columns)
                      dfb_tmp = dfb[dfb['StockID'].notnull()]
                      
                      def myfunc(row):
                          # NB: Use row.name because row['StockID'] is the index
                          if row.name in list(dfb_tmp['StockID']):
                              return dfb_tmp.loc[dfb_tmp['StockID'] == row.name]['Category'].values[0]
                      dfa['Cat'] = dfa.apply(lambda row: myfunc(row), axis=1)
                      
                      print(dfa)
                      
                      
                      StockID Brand   ToolName    Price   Cat
                      ABC123  Maxwell ToolA       1.25    CatThis
                      BCD234  Charton ToolB       2.22    CatShop
                      CDE345  Bingley ToolC       3.33    CatThings
                      DEF789  Charton ToolD       1.44    CatShop
                      
                      import pandas as pd
                      dfa = pd.read_csv('csv_a.csv')
                      dfa.set_index('StockID', inplace=True)
                      dfb = pd.read_csv('csv_b.csv')
                      
                      #remove incomplete rows (i.e. without Category/StockID columns)
                      dfb_tmp = dfb[dfb['StockID'].notnull()]
                      
                      def myfunc(row):
                          # NB: Use row.name because row['StockID'] is the index
                          if row.name in list(dfb_tmp['StockID']):
                              return dfb_tmp.loc[dfb_tmp['StockID'] == row.name]['Category'].values[0]
                      dfa['Cat'] = dfa.apply(lambda row: myfunc(row), axis=1)
                      
                      print(dfa)
                      
                      
                      StockID Brand   ToolName    Price   Cat
                      ABC123  Maxwell ToolA       1.25    CatThis
                      BCD234  Charton ToolB       2.22    CatShop
                      CDE345  Bingley ToolC       3.33    CatThings
                      DEF789  Charton ToolD       1.44    CatShop
                      
                      df_a['Cat'] = df_a['StockID'].map(dict(zip(df_b['StockID'], df_b['Category'])))
                      
                      df_a['Cat'] = df_a.index.map(dict(zip(df_b['StockID'], df_b['Category'])))
                                         ^^^^^
                      
                      df_a['Cat'] = df_a['StockID'].map(dict(zip(df_b['StockID'], df_b['Category'])))
                      
                      df_a['Cat'] = df_a.index.map(dict(zip(df_b['StockID'], df_b['Category'])))
                                         ^^^^^
                      

                      No any output from hello world of node.js redis

                      copy iconCopydownload iconDownload
                      (async () => {
                        const client = createClient();
                      
                        client.on('error', (err) => console.log('Redis Client Error', err));
                      
                        await client.connect();
                      
                        await client.set('key', 'value');
                        const value = await client.get('key');
                        await client.quit();
                      })();
                      

                      Plotting Maxwellian Distribution in Julia

                      copy iconCopydownload iconDownload
                      julia> (m_e/(2*pi*k*T_M))^1.5
                      1.0769341115495682e-27
                      
                      julia> ylims!(-1e-28, 2e-27)
                      
                      julia> (m_e/(2*pi*k*T_M))^1.5
                      1.0769341115495682e-27
                      
                      julia> ylims!(-1e-28, 2e-27)
                      

                      How do i populate three sections in a tableview with SwiftyJSON

                      copy iconCopydownload iconDownload
                      struct Section {
                          let name : String
                          let users : [User]
                      }
                      
                      struct User : Decodable {
                          let name, password, username, authority : String
                          let id : Int
                      }
                      
                      var sections = [Section]()
                      
                      let jsonString = """
                      [{
                        "name" : "Oliver",
                        "password" : "1234",
                        "username" : "Ramy",
                        "id" : 84560,
                        "authority" : "Manager"
                      }, {
                        "name" : "Maxwell",
                        "password" : "1234",
                        "username" : "Omar",
                        "id" : 84561,
                        "authority" : "Accountant"
                      }, {
                        "name" : "Tom",
                        "password" : "1234",
                        "username" : "Ahmed",
                        "id" : 84562,
                        "authority" : "Accountant"
                      }]
                      """
                      
                      do {
                          let users = try JSONDecoder().decode([User].self, from: Data(jsonString.utf8))
                          let grouped = Dictionary(grouping: users, by: \.authority)
                          sections = grouped.map(Section.init)
                          
                          print(sections)
                      } catch {
                          print(error)
                      }
                      
                      func numberOfSections(in tableView: UITableView) -> Int {
                          return sections.count
                      }
                      
                      func tableView(_ tableView: UITableView, numberOfRowsInSection section: Int) -> Int {
                          return sections[section].users.count
                      }
                      
                      func tableView(_ tableView: UITableView, cellForRowAt indexPath: IndexPath) -> UITableViewCell {
                          let cell = tableView.dequeueReusableCell(withIdentifier: "usersTVC", for: indexPath)
                          let user = sections[indexPath.section].users[indexPath.row]
                          cell.textLabel?.text = "ID: \(user.id) - \(user.name)"
                          return cell
                      }
                      
                      AF.request(url, method: .post, parameters: data, headers: headers).responseDecodable(of: [User].self, decoder: JSONDecoder()) { response in
                          switch response.result {
                              case .success(let users): 
                                 let grouped = Dictionary(grouping: users, by: \.authority)
                                 sections = grouped.map(Section.init)
                              case .failure(let error): print(error)
                          
                      
                      struct Section {
                          let name : String
                          let users : [User]
                      }
                      
                      struct User : Decodable {
                          let name, password, username, authority : String
                          let id : Int
                      }
                      
                      var sections = [Section]()
                      
                      let jsonString = """
                      [{
                        "name" : "Oliver",
                        "password" : "1234",
                        "username" : "Ramy",
                        "id" : 84560,
                        "authority" : "Manager"
                      }, {
                        "name" : "Maxwell",
                        "password" : "1234",
                        "username" : "Omar",
                        "id" : 84561,
                        "authority" : "Accountant"
                      }, {
                        "name" : "Tom",
                        "password" : "1234",
                        "username" : "Ahmed",
                        "id" : 84562,
                        "authority" : "Accountant"
                      }]
                      """
                      
                      do {
                          let users = try JSONDecoder().decode([User].self, from: Data(jsonString.utf8))
                          let grouped = Dictionary(grouping: users, by: \.authority)
                          sections = grouped.map(Section.init)
                          
                          print(sections)
                      } catch {
                          print(error)
                      }
                      
                      func numberOfSections(in tableView: UITableView) -> Int {
                          return sections.count
                      }
                      
                      func tableView(_ tableView: UITableView, numberOfRowsInSection section: Int) -> Int {
                          return sections[section].users.count
                      }
                      
                      func tableView(_ tableView: UITableView, cellForRowAt indexPath: IndexPath) -> UITableViewCell {
                          let cell = tableView.dequeueReusableCell(withIdentifier: "usersTVC", for: indexPath)
                          let user = sections[indexPath.section].users[indexPath.row]
                          cell.textLabel?.text = "ID: \(user.id) - \(user.name)"
                          return cell
                      }
                      
                      AF.request(url, method: .post, parameters: data, headers: headers).responseDecodable(of: [User].self, decoder: JSONDecoder()) { response in
                          switch response.result {
                              case .success(let users): 
                                 let grouped = Dictionary(grouping: users, by: \.authority)
                                 sections = grouped.map(Section.init)
                              case .failure(let error): print(error)
                          
                      
                      struct Section {
                          let name : String
                          let users : [User]
                      }
                      
                      struct User : Decodable {
                          let name, password, username, authority : String
                          let id : Int
                      }
                      
                      var sections = [Section]()
                      
                      let jsonString = """
                      [{
                        "name" : "Oliver",
                        "password" : "1234",
                        "username" : "Ramy",
                        "id" : 84560,
                        "authority" : "Manager"
                      }, {
                        "name" : "Maxwell",
                        "password" : "1234",
                        "username" : "Omar",
                        "id" : 84561,
                        "authority" : "Accountant"
                      }, {
                        "name" : "Tom",
                        "password" : "1234",
                        "username" : "Ahmed",
                        "id" : 84562,
                        "authority" : "Accountant"
                      }]
                      """
                      
                      do {
                          let users = try JSONDecoder().decode([User].self, from: Data(jsonString.utf8))
                          let grouped = Dictionary(grouping: users, by: \.authority)
                          sections = grouped.map(Section.init)
                          
                          print(sections)
                      } catch {
                          print(error)
                      }
                      
                      func numberOfSections(in tableView: UITableView) -> Int {
                          return sections.count
                      }
                      
                      func tableView(_ tableView: UITableView, numberOfRowsInSection section: Int) -> Int {
                          return sections[section].users.count
                      }
                      
                      func tableView(_ tableView: UITableView, cellForRowAt indexPath: IndexPath) -> UITableViewCell {
                          let cell = tableView.dequeueReusableCell(withIdentifier: "usersTVC", for: indexPath)
                          let user = sections[indexPath.section].users[indexPath.row]
                          cell.textLabel?.text = "ID: \(user.id) - \(user.name)"
                          return cell
                      }
                      
                      AF.request(url, method: .post, parameters: data, headers: headers).responseDecodable(of: [User].self, decoder: JSONDecoder()) { response in
                          switch response.result {
                              case .success(let users): 
                                 let grouped = Dictionary(grouping: users, by: \.authority)
                                 sections = grouped.map(Section.init)
                              case .failure(let error): print(error)
                          
                      
                      struct Section {
                          let name : String
                          let users : [User]
                      }
                      
                      struct User : Decodable {
                          let name, password, username, authority : String
                          let id : Int
                      }
                      
                      var sections = [Section]()
                      
                      let jsonString = """
                      [{
                        "name" : "Oliver",
                        "password" : "1234",
                        "username" : "Ramy",
                        "id" : 84560,
                        "authority" : "Manager"
                      }, {
                        "name" : "Maxwell",
                        "password" : "1234",
                        "username" : "Omar",
                        "id" : 84561,
                        "authority" : "Accountant"
                      }, {
                        "name" : "Tom",
                        "password" : "1234",
                        "username" : "Ahmed",
                        "id" : 84562,
                        "authority" : "Accountant"
                      }]
                      """
                      
                      do {
                          let users = try JSONDecoder().decode([User].self, from: Data(jsonString.utf8))
                          let grouped = Dictionary(grouping: users, by: \.authority)
                          sections = grouped.map(Section.init)
                          
                          print(sections)
                      } catch {
                          print(error)
                      }
                      
                      func numberOfSections(in tableView: UITableView) -> Int {
                          return sections.count
                      }
                      
                      func tableView(_ tableView: UITableView, numberOfRowsInSection section: Int) -> Int {
                          return sections[section].users.count
                      }
                      
                      func tableView(_ tableView: UITableView, cellForRowAt indexPath: IndexPath) -> UITableViewCell {
                          let cell = tableView.dequeueReusableCell(withIdentifier: "usersTVC", for: indexPath)
                          let user = sections[indexPath.section].users[indexPath.row]
                          cell.textLabel?.text = "ID: \(user.id) - \(user.name)"
                          return cell
                      }
                      
                      AF.request(url, method: .post, parameters: data, headers: headers).responseDecodable(of: [User].self, decoder: JSONDecoder()) { response in
                          switch response.result {
                              case .success(let users): 
                                 let grouped = Dictionary(grouping: users, by: \.authority)
                                 sections = grouped.map(Section.init)
                              case .failure(let error): print(error)
                          
                      
                      struct Section {
                          let name : String
                          let users : [User]
                      }
                      
                      struct User : Decodable {
                          let name, password, username, authority : String
                          let id : Int
                      }
                      
                      var sections = [Section]()
                      
                      let jsonString = """
                      [{
                        "name" : "Oliver",
                        "password" : "1234",
                        "username" : "Ramy",
                        "id" : 84560,
                        "authority" : "Manager"
                      }, {
                        "name" : "Maxwell",
                        "password" : "1234",
                        "username" : "Omar",
                        "id" : 84561,
                        "authority" : "Accountant"
                      }, {
                        "name" : "Tom",
                        "password" : "1234",
                        "username" : "Ahmed",
                        "id" : 84562,
                        "authority" : "Accountant"
                      }]
                      """
                      
                      do {
                          let users = try JSONDecoder().decode([User].self, from: Data(jsonString.utf8))
                          let grouped = Dictionary(grouping: users, by: \.authority)
                          sections = grouped.map(Section.init)
                          
                          print(sections)
                      } catch {
                          print(error)
                      }
                      
                      func numberOfSections(in tableView: UITableView) -> Int {
                          return sections.count
                      }
                      
                      func tableView(_ tableView: UITableView, numberOfRowsInSection section: Int) -> Int {
                          return sections[section].users.count
                      }
                      
                      func tableView(_ tableView: UITableView, cellForRowAt indexPath: IndexPath) -> UITableViewCell {
                          let cell = tableView.dequeueReusableCell(withIdentifier: "usersTVC", for: indexPath)
                          let user = sections[indexPath.section].users[indexPath.row]
                          cell.textLabel?.text = "ID: \(user.id) - \(user.name)"
                          return cell
                      }
                      
                      AF.request(url, method: .post, parameters: data, headers: headers).responseDecodable(of: [User].self, decoder: JSONDecoder()) { response in
                          switch response.result {
                              case .success(let users): 
                                 let grouped = Dictionary(grouping: users, by: \.authority)
                                 sections = grouped.map(Section.init)
                              case .failure(let error): print(error)
                          
                      

                      how to fix template does not exist in Django?

                      copy iconCopydownload iconDownload
                      def html(request):
                          return render(request, 'Blog/index.html')
                      TEMPLATES = [
                          {
                              ...
                              'DIRS': [os.path.join(BASE_DIR,'templates')],#add this line
                              ...
                      ]
                      
                      return render(request,"template_folder/template_name.html")
                      
                      TEMPLATES = [
                          {
                              ...
                              'DIRS': [os.path.join(BASE_DIR,'templates')],#add this line
                              ...
                      ]
                      
                      return render(request,"template_folder/template_name.html")
                      

                      Collect similar terms in sympy

                      copy iconCopydownload iconDownload
                      In [2]: e, a, m, n = symbols('e, a, m, n')
                      
                      In [3]: sol = solveset(Eq((e-m)/(e+2*m), n*(a-m)/(a+2*m)), m)
                      
                      In [4]: s1, s2 = sol.args[0]
                      
                      In [5]: s1
                      Out[5]: 
                                                 _____________________________________________________________________________
                                                ╱    2  2      2      2          2                       2  2      2        2 
                      2⋅a⋅n + a - e⋅n - 2⋅e   ╲╱  4⋅a ⋅n  + 4⋅a ⋅n + a  + 4⋅a⋅e⋅n  - 26⋅a⋅e⋅n + 4⋅a⋅e + e ⋅n  + 4⋅e ⋅n + 4⋅e  
                      ───────────────────── - ────────────────────────────────────────────────────────────────────────────────
                            4⋅(n - 1)                                            4⋅(n - 1)                                    
                      
                      In [6]: s1.collect(e, lambda c: c.factor() if c.is_polynomial() else c)
                      Out[6]: 
                                                    _______________________________________________________
                                                   ╱  2          2         ⎛   2           ⎞    2        2 
                      a⋅(2⋅n + 1) + e⋅(-n - 2)   ╲╱  a ⋅(2⋅n + 1)  + 2⋅a⋅e⋅⎝2⋅n  - 13⋅n + 2⎠ + e ⋅(n + 2)  
                      ──────────────────────── - ──────────────────────────────────────────────────────────
                             4⋅(n - 1)                                   4⋅(n - 1)                         
                      
                      In [7]: s2.collect(e, lambda c: c.factor() if c.is_polynomial() else c)
                      Out[7]: 
                                                    _______________________________________________________
                                                   ╱  2          2         ⎛   2           ⎞    2        2 
                      a⋅(2⋅n + 1) + e⋅(-n - 2)   ╲╱  a ⋅(2⋅n + 1)  + 2⋅a⋅e⋅⎝2⋅n  - 13⋅n + 2⎠ + e ⋅(n + 2)  
                      ──────────────────────── + ──────────────────────────────────────────────────────────
                             4⋅(n - 1)                                   4⋅(n - 1) 
                      

                      D3.js style and class override not work as my expectation

                      copy iconCopydownload iconDownload
                      d3.select("table").select("tr").selectAll("td").classed("bold-header", true);
                      
                      d3.select("table").selectAll("tr:not(:first-child)").style("background-color", "lightblue").style("width", "100px");
                      
                      d3.select("table").select("tr").classed("bold-header", true);
                       .bold-header{
                              background-color:navy;
                              color:white;
                          }
                      <script src="https://cdnjs.cloudflare.com/ajax/libs/d3/5.7.0/d3.min.js"></script>
                      <table border="1">
                          <tr>
                              <td>ID</td>
                              <td>Name</td>
                          </tr>
                          <tr>
                              <td>001</td>
                              <td>John</td>
                          </tr>
                          <tr>
                              <td>002</td>
                              <td>Alex</td>
                          </tr>
                          <tr>         
                              <td>003</td>
                              <td>Maxwell</td>
                          </tr>
                      </table>
                      d3.select("table").select("tr").selectAll("td").classed("bold-header", true);
                      
                      d3.select("table").selectAll("tr:not(:first-child)").style("background-color", "lightblue").style("width", "100px");
                      
                      d3.select("table").select("tr").classed("bold-header", true);
                       .bold-header{
                              background-color:navy;
                              color:white;
                          }
                      <script src="https://cdnjs.cloudflare.com/ajax/libs/d3/5.7.0/d3.min.js"></script>
                      <table border="1">
                          <tr>
                              <td>ID</td>
                              <td>Name</td>
                          </tr>
                          <tr>
                              <td>001</td>
                              <td>John</td>
                          </tr>
                          <tr>
                              <td>002</td>
                              <td>Alex</td>
                          </tr>
                          <tr>         
                              <td>003</td>
                              <td>Maxwell</td>
                          </tr>
                      </table>
                      d3.select("table").select("tr").selectAll("td").classed("bold-header", true);
                      
                      d3.select("table").selectAll("tr:not(:first-child)").style("background-color", "lightblue").style("width", "100px");
                      
                      d3.select("table").select("tr").classed("bold-header", true);
                       .bold-header{
                              background-color:navy;
                              color:white;
                          }
                      <script src="https://cdnjs.cloudflare.com/ajax/libs/d3/5.7.0/d3.min.js"></script>
                      <table border="1">
                          <tr>
                              <td>ID</td>
                              <td>Name</td>
                          </tr>
                          <tr>
                              <td>001</td>
                              <td>John</td>
                          </tr>
                          <tr>
                              <td>002</td>
                              <td>Alex</td>
                          </tr>
                          <tr>         
                              <td>003</td>
                              <td>Maxwell</td>
                          </tr>
                      </table>
                      d3.select("table").select("tr").selectAll("td").classed("bold-header", true);
                      
                      d3.select("table").selectAll("tr:not(:first-child)").style("background-color", "lightblue").style("width", "100px");
                      
                      d3.select("table").select("tr").classed("bold-header", true);
                       .bold-header{
                              background-color:navy;
                              color:white;
                          }
                      <script src="https://cdnjs.cloudflare.com/ajax/libs/d3/5.7.0/d3.min.js"></script>
                      <table border="1">
                          <tr>
                              <td>ID</td>
                              <td>Name</td>
                          </tr>
                          <tr>
                              <td>001</td>
                              <td>John</td>
                          </tr>
                          <tr>
                              <td>002</td>
                              <td>Alex</td>
                          </tr>
                          <tr>         
                              <td>003</td>
                              <td>Maxwell</td>
                          </tr>
                      </table>

                      EASY: How do I separate elements grabbed by class name using Selenium Webdriver?

                      copy iconCopydownload iconDownload
                      driver.find_elements_by_css_selector('.sceneColActors a')
                      
                      driver.find_elements_by_class_name('sceneColActors')
                      
                      driver.find_elements_by_css_selector('.sceneColActors a')
                      
                      driver.find_elements_by_class_name('sceneColActors')
                      

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                      QUESTION

                      Could not find any factory for identifier 'avro-confluent' that implements 'org.apache.flink.table.factories.DeserializationFormatFactory'

                      Asked 2022-Feb-27 at 19:32

                      I have a Flink job that runs well locally but fails when I try to flink run the job on cluster. The error happens when trying to load data from Kafka via 'connector' = 'kafka'. I am using Flink-Table API and confluent-avro format for reading data from Kafka.

                      So basically i created a table which reads data from kafka topic:

                          val inputTableSQL =
                            s"""CREATE TABLE input_table (
                               |  -- key of the topic
                               |  key BYTES NOT NULL,
                               |
                               |  -- a few columns mapped to the Avro fields of the Kafka value
                               |  id STRING,
                               |
                               |) WITH (
                               |
                               |  'connector' = 'kafka',
                               |  'topic' = '${KafkaConfiguration.InputTopicName}',
                               |  'scan.startup.mode' = 'latest-offset',
                               |
                               |  -- UTF-8 string as Kafka keys, using the 'key' table column
                               |  'key.format' = 'raw',
                               |  'key.fields' = 'key',
                               |
                               |  'value.format' = 'avro-confluent',
                               |  'value.avro-confluent.schema-registry.url' = '${KafkaConfiguration.KafkaConsumerSchemaRegistryUrl}',
                               |  'value.fields-include' = 'EXCEPT_KEY'
                               |)
                               |""".stripMargin
                          val inputTable = tableEnv.executeSql(inputTableSQL)
                      

                      and then i created another table, which i will use as output table:

                      val outputTableSQL =
                            s"""CREATE TABLE custom_avro_output_table (
                               |  -- key of the topic
                               |  key BYTES NOT NULL,
                               |
                               |  -- a few columns mapped to the Avro fields of the Kafka value
                               |  ID STRING
                               |) WITH (
                               |
                               |  'connector' = 'kafka',
                               |  'topic' = '${KafkaConfiguration.OutputTopicName}',
                               |  'properties.bootstrap.servers' = '${KafkaConfiguration.KafkaProducerBootstrapServers}',
                               |
                               |  -- UTF-8 string as Kafka keys, using the 'key' table column
                               |  'key.format' = 'raw',
                               |  'key.fields' = 'key',
                               |
                               |  $outputFormatSettings
                               |  'value.fields-include' = 'EXCEPT_KEY'
                               |)
                               |""".stripMargin
                      
                          val outputTableCreationResult = tableEnv.executeSql(outputTableSQL)
                          
                      val customInsertSQL =
                            """INSERT INTO custom_avro_output_table
                              |SELECT key, id
                              |  FROM input_table
                              | WHERE userAgent LIKE '%ost%'
                              |""".stripMargin
                      
                          val customInsertResult = tableEnv.executeSql(customInsertSQL)
                      

                      when i run this in local machine, everything works fine, but when i run it in cluster, it crashes.

                          at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) ~[?:1.8.0_282]
                          at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) ~[?:1.8.0_282]
                          at java.lang.reflect.Method.invoke(Method.java:498) ~[?:1.8.0_282]
                          at org.apache.flink.client.program.PackagedProgram.callMainMethod(PackagedProgram.java:355) ~[flink-dist_2.12-1.13.1.jar:1.13.1]
                          ... 13 more
                      Caused by: org.apache.flink.table.api.ValidationException: Could not find any factory for identifier 'avro-confluent' that implements 'org.apache.flink.table.factories.DeserializationFormatFactory' in the classpath.
                      
                      Available factory identifiers are:
                      
                      canal-json
                      csv
                      debezium-json
                      json
                      maxwell-json
                      raw
                          at org.apache.flink.table.factories.FactoryUtil.discoverFactory(FactoryUtil.java:319) ~[flink-table_2.12-1.13.1.jar:1.13.1]
                          at org.apache.flink.table.factories.FactoryUtil$TableFactoryHelper.discoverOptionalFormatFactory(FactoryUtil.java:751) ~[flink-table_2.12-1.13.1.jar:1.13.1]
                          at org.apache.flink.table.factories.FactoryUtil$TableFactoryHelper.discoverOptionalDecodingFormat(FactoryUtil.java:649) ~[flink-table_2.12-1.13.1.jar:1.13.1]
                          at org.apache.flink.table.factories.FactoryUtil$TableFactoryHelper.discoverDecodingFormat(FactoryUtil.java:633) ~[flink-table_2.12-1.13.1.jar:1.13.1]
                          at org.apache.flink.streaming.connectors.kafka.table.KafkaDynamicTableFactory.lambda$getValueDecodingFormat$2(KafkaDynamicTableFactory.java:279) ~[?:?]
                          at java.util.Optional.orElseGet(Optional.java:267) ~[?:1.8.0_282]
                          at org.apache.flink.streaming.connectors.kafka.table.KafkaDynamicTableFactory.getValueDecodingFormat(KafkaDynamicTableFactory.java:277) ~[?:?]
                          at org.apache.flink.streaming.connectors.kafka.table.KafkaDynamicTableFactory.createDynamicTableSource(KafkaDynamicTableFactory.java:142) ~[?:?]
                          at org.apache.flink.table.factories.FactoryUtil.createTableSource(FactoryUtil.java:134) ~[flink-table_2.12-1.13.1.jar:1.13.1]
                          at org.apache.flink.table.planner.plan.schema.CatalogSourceTable.createDynamicTableSource(CatalogSourceTable.java:116) ~[flink-table-blink_2.12-1.13.1.jar:1.13.1]
                          at org.apache.flink.table.planner.plan.schema.CatalogSourceTable.toRel(CatalogSourceTable.java:82) ~[flink-table-blink_2.12-1.13.1.jar:1.13.1]
                          at org.apache.calcite.sql2rel.SqlToRelConverter.toRel(SqlToRelConverter.java:3585) ~[flink-table_2.12-1.13.1.jar:1.13.1]
                      
                      

                      following is my build.sbt:

                      val flinkVersion = "1.13.1"
                      
                      val flinkDependencies = Seq(
                        "org.apache.flink" %% "flink-scala" % flinkVersion % Provided,
                        "org.apache.flink" %% "flink-streaming-scala" % flinkVersion % Provided,
                        "org.apache.flink" %% "flink-connector-kafka" % flinkVersion,
                        "org.apache.flink" %% "flink-clients" % flinkVersion % Provided,
                        "org.apache.flink" %% "flink-table-api-scala-bridge" % flinkVersion % Provided,
                        "org.apache.flink" %% "flink-table-planner-blink"  % flinkVersion % Provided,
                        "org.apache.flink" % "flink-table-common"  % flinkVersion % Provided,
                        "org.apache.flink" % "flink-avro-confluent-registry" % flinkVersion,
                        "org.apache.flink" % "flink-json" % flinkVersion,
                        "com.webtrekk" % "wd.generated" % "2.2.3",
                        "com.webtrekk" % "wd.generated.public" % "2.2.0",
                        "ch.qos.logback" % "logback-classic" % "1.2.3"
                      )
                      

                      ANSWER

                      Answered 2021-Oct-26 at 17:47

                      I was able to fix this problem using following approach:

                      In my build.sbt, there was the following mergeStrategy:

                      lazy val mergeStrategy = Seq(
                        assembly / assemblyMergeStrategy := {
                          case "application.conf" => MergeStrategy.concat
                          case "reference.conf" => MergeStrategy.concat
                          case m if m.toLowerCase.endsWith("manifest.mf") => MergeStrategy.discard
                          case m if m.toLowerCase.matches("meta-inf.*\\.sf$") => MergeStrategy.discard
                          case _ => MergeStrategy.first
                        }
                      )
                      

                      I appended the following chunk in it, hence resolved my exception:

                      case "META-INF/services/org.apache.flink.table.factories.Factory"  => MergeStrategy.concat
                      case "META-INF/services/org.apache.flink.table.factories.TableFactory"  => MergeStrategy.concat
                      

                      Source https://stackoverflow.com/questions/69677946

                      Community Discussions, Code Snippets contain sources that include Stack Exchange Network

                      Vulnerabilities

                      No vulnerabilities reported

                      Install maxwell

                      You can download it from GitHub, Maven.
                      You can use maxwell like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the maxwell component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

                      Support

                      For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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